Orientation Independent Sensing, Mapping, Interface and Analysis Systems and Methods

ABSTRACT

The disclosure relates generally to applications of Orientation Independent Sensing (OIS) and Omnipolar mapping Technology (OT) to various system, device and method embodiments as recited herein. Similarly, systems and methods suitable for supporting OIS and OT systems and methods are disclosed. Further, OIS and OT implementations that provide end user interfaces, diagnostic indicia and visual displays generated, in part, based on measured data or derived from measured data are also disclosed. Embodiments also describe applying optimization techniques to determine the greatest voltage difference of a local electric field associated with an electrode-based diagnostic procedure and a vector representation thereof. Various graphic user interface related features are also described to facilitate orientation and electrode clique signal display.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to and the benefit of U.S. provisionalpatent application No. 62/485,875, filed on Apr. 14, 2017, thedisclosure of which is herein incorporated by reference in its entirety.

FIELD

In part, the disclosure relates generally to the field of vascularsystem and data collection and analysis relating thereto. Moreparticularly, the disclosure relates, in part, to systems and methods tomeasure and analyze diagnostic information of interest based uponelectrophysiology data.

BACKGROUND

Electrophysiology (EP) catheters are used in a variety of diagnostic,therapeutic, and/or mapping and ablative procedures to diagnose and/orcorrect conditions such as atrial or ventricular arrhythmias, includingfor example, ectopic atrial tachycardia, atrial fibrillation, and atrialflutter. Arrhythmias can create a variety of conditions includingirregular heart rates, loss of synchronous atrioventricular contractionsand stasis of blood flow in a chamber of a heart which can lead to avariety of symptomatic and asymptomatic ailments and even death.

Typically, a catheter is deployed and manipulated through a patient'svasculature to the intended site, for example, a site within a patient'sheart. The catheter carries one or more electrodes that can be used forcardiac mapping or diagnosis, ablation and/or other therapy deliverymodes, or both, for example. Once at the intended site, treatment caninclude, for example, radio frequency (RF) ablation, cryoablation, laserablation, chemical ablation, high-intensity focused ultrasound-basedablation, microwave ablation, and/or other ablation treatments. Thecatheter imparts ablative energy to cardiac tissue to create one or morelesions in the cardiac tissue. To position a catheter at a desired sitewithin the body, some type of navigation may be used, such as usingmechanical steering features incorporated into the catheter (or asheath). In some examples, medical personnel may manually manipulateand/or operate the catheter using the mechanical steering features.

Various catheter designs, such as for example, spline-based catheterswith an array of electrodes, can be used to perform voltage mappingrelative to the cardiac system as noted above. Voltage mapping is animportant clinical tool to evaluate arrhythmogenic myocardium and guidesfurther diagnostic and therapeutic procedures. It is most oftenconducted using bipoles; however, the challenges of directionaldependence and electrode spacing irregularity when using bipole-basedsignals can result in suboptimal data collection and erroneous signalprocessing.

In part, the present disclosure addresses these challenges and others,in part, by extending omnipolar-based systems and methods for use withvoltage mapping and other tissue sensing related systems and methods asrecited herein.

SUMMARY

The foregoing discussion is intended only to illustrate the presentfield and should not be taken as a disavowal of claim scope. Thedisclosure relates generally to applications of Orientation IndependentSensing (OIS) and Omnipolar mapping Technology (OT) to various system,device and method embodiments as recited herein. In one embodiment, thedisclosure relates to systems and method of reducing one or more typesof error associated with electrophysiology data acquired from a subject.

In part, the disclosure relates to a method of reducing one or moreerror types in cardiac system data obtained from a subject using aplurality of electrodes. The method includes defining an error reducingvector {circumflex over (m)} by normalizing a differential electricfield vector using a magnitude, wherein the differential electric fieldvector is a difference of a first electric field vector E(t_(j)) and asecond electric field vector E(t_(i)), wherein t_(i) and t_(j) areelectric field measurements in time, wherein t_(j)>t_(i) and wherein themagnitude is |E(t_(j))−E(t_(i))|; determining a cardiac system parameterby performing a vector operation comprising operating, using anoperator, upon (i) {circumflex over (m)} or a vector perpendicularthereto {circumflex over (m)}_(⊥) and (ii) a diagnostic vector, whereinthe diagnostic vector is generated using measured cardiac electrogramsignals to generate an output, wherein the output is a scalar output ora vector output; and displaying the output or information correlatedwith the output. In one embodiment, the method further comprisesmaximizing |E(t_(j))−E(t_(i))|.

In one embodiment, the operator is a dot product operator, wherein thediagnostic vector is E(t), and wherein the output of ({circumflex over(m)},E(t) is a scalar electrical field signal E_(m)(t). In oneembodiment, the method further comprises computing a peak to peak valueof E_(m)(t).

In one embodiment, the method further comprises determining a scalarvoltage signal Vm(t), wherein Vm(t) comprises a product of k andE_(m)(t), wherein k is an electrode spacing between the plurality ofelectrodes. In one embodiment, the method further comprises computing apeak to peak value of V_(m)(t). In one embodiment, the operator is a dotproduct operator, wherein the diagnostic vector is E(t), and wherein theoutput of <{circumflex over (m)}⊥,E(t)> is a scalar electrical fieldsignal E_(m⊥)(t).

In one embodiment, the method further comprises determining one or moredirectional deviations between {circumflex over (m)} and â andgenerating an alert when the one or more directional deviations exceedsa threshold, wherein the direction of â is an activation direction. Inone embodiment, the threshold is an angular deviation between thatranges from about 15 degrees to about 20 degrees.

In one embodiment, the one or more error types includedirectionality-based errors and further comprising reducingdirectionality-based errors. In one embodiment, the method furthercomprises displaying one or more graphic user interface elementscorresponding to or aligned with {circumflex over (m)} relative to a 2Dor 3D display of a cardiac tissue representation. In one embodiment, themethod further comprises displaying the one or more graphic userinterface elements corresponding to or aligned with {circumflex over(m)} relative to one or more regions of detected cardiac tissueactivation. In one embodiment, the method further comprises displaying agraphic user interface element that comprises a plurality of userselectable elements, wherein the user selectable elements comprise aplurality of triangular electrode cliques and a plurality of squareelectrode cliques.

In one embodiment, in response to user selection of one or more of thesquare electrode cliques or triangular electrode cliques, one or morewaveforms associated with each clique selected is displayed. In oneembodiment, the graphic user interface element is a guide diagramcomprising a representation of an array of electrodes for a diagnosticcatheter and one or more indicia, wherein the indicia corresponds to aparameter selected from the group consisting of a bipole voltage, aunipole voltage, a unipole wave form, a bipole waveform, an ablationgap, and an activation direction. In one embodiment, the indicium is acolor and further comprising displaying a color coded legend comprisingthe color. Various other indicia may be used, without limitation, suchas hatching, bolding, and other visual cues or graphical user interfaceelements. This broad range of possible indicia applies to all userinterface and visual representations described or depicted herein.

In part, the disclosure relates to a method of determining diagnosticinformation for a subject using a plurality of electrode-basedmeasurements. The method includes storing, in one or more electronicmemory storage devices, one or more sets of electrophysiological (EP)data received with regard to one or more tissues of the subject, whereinthe one or more sets comprise a first set of EP data; determining a setof electric field data from the first set of EP data, wherein the set ofelectric field data comprises a plurality of time varying electric fieldvectors; computing, for each pair of temporally adjacent electric fieldvectors of the plurality of time varying electric field vectors, adifference vector, wherein each difference vector has differentialmagnitude, identifying, from differential magnitudes of differencevectors, a relative extremum of the differential magnitudes, as a firstdifferential magnitude; defining a first diagnostic parameter,{circumflex over (m)}, wherein {circumflex over (m)} is proportional toor equal to the difference vector having the first differentialmagnitude; and displaying graphic user face element oriented along adirection of {circumflex over (m)}. In one embodiment, the methodfurther includes determining a second diagnostic parameter is (i) usinga vector operator and {circumflex over (m)} or (ii) a vector correlatedwith {circumflex over (m)} or derived therefrom.

In part, the disclosure relates to a method of generating a referencesignal suitable for comparison to one or more cardiac tissue measuredsignals. The method includes selecting a clique of connected unipoles ina non-linear arrangement; converting combination of selected unipolesand associated bipoles to electric field components; and convertingelectric field components to electrical potential signals V_(x) andV_(y), wherein x and y are axes of catheter reference frame.

In one embodiment, the method further includes normalizing V_(x) andV_(y) signals to generate a direction independent signal. In oneembodiment, the method further includes filtering the directionindependent signal to generate a filtered direction independent signal,wherein the filtered signal is directionally independent. In oneembodiment, the step of filtering comprises one or more steps selectedfrom the group consisting of reducing an error associated with detectionof depolarizations, low pass filtering, differentiating, and signalthresholding.

In one embodiment, the method further includes processing the filtereddirection independent signal using a refractory period of cardiactissue, a noise floor, and a zero-crossing detector to detectpolarization events in the filtered signal. In one embodiment, thenormalizing step comprises determining a Euclidean magnitude. In oneembodiment, the step of converting the combination of selected unipolesand associated bipoles is performed by performing a least squares fit.In one embodiment, the method further includes measuring a plurality ofelectrical signals from cardiac tissue during atrial fibrillation andcharacterizing spatial coherence of a vector field derived using thecardiac system parameter.

In one embodiment, the step of characterizing is performed using acoherence or entropy measurement of one or more vectors of the vectorfield. In one embodiment, the step of characterizing is performed bycoherence filtering Vmax values on a per cycle basis and comparingfiltered results for each cycle to exclude inconsistent regions betweendifferent cycles.

In one embodiment, one or more methods include identifying ablation linegaps. In one embodiment, one or more methods include mapping a scarborder, isthmus within scar or locus. In one embodiment, one or moremethods include assessing an atrial substrate, in regular sinus rhythmand also during atrial fibrillation. In one embodiment, one or moremethods include locating a reentrant entrance site or exit site.

Although, the invention relates to different aspects and embodiments, itis understood that the different aspects and embodiments disclosedherein can be integrated together as a whole or in part, as appropriate.Thus, each embodiment disclosed herein can be incorporated in each ofthe aspects to varying degrees as appropriate for a given implementationand steps from various methods can be combined without limitation.Notwithstanding the foregoing and the other disclosure herein,embodiments disclosed herein may also be applied in the context ofbipolar based systems and methods as applicable.

Other features and advantages of the disclosed embodiments will beapparent from the following description and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1A is a diagrammatic view of a system for generating surfacemodels, mapping electrophysiological information thereon, and/orproviding user interfaces, diagnostic information, electrophysiologicalvector representations, and positional information.

FIG. 1B is simplified diagrammatic and schematic view of the systemillustrated in FIG. 1A.

FIG. 2A is an isometric view of one embodiment of an exemplary catheterhaving electrodes groupable into square and triangular cliques accordingto an illustrative embodiment.

FIG. 2B is a zoomed in view of four electrodes suitable for grouping assquare or triangular cliques relative to a catheter reference frame forreference trigger generation and relationships for determiningdirectional bipole signals along catheter axes.

FIG. 3 is a graph of an E(t) loop in 3D that includes m-hat oriented inthe direction of maximum (or relative extremum) peak-peak voltage andelectric field magnitude.

FIG. 4 is an illustration showing the activation, wave crest, surfacenormal, and conduction velocity directions for a traveling wave relativeto a vector m-hat and an angular deviation relative to a-hat.

FIG. 5 is a flow chart showing a method to generate m-hat and a relatedOT metric Vm(t) using a reference trigger or reference signal.

FIG. 6 is a schematic illustrating electrode location andrepresentations of m-hat in the context of both catheter and 3D bodycoordinate frames (involving rotation and translation).

FIG. 7A is a block diagram of a system suitable for generating areference trigger or reference signal.

FIG. 7B is a flow chart showing a method to generate an orientationindependent reference trigger or reference signal from a combination ofunipole signals and bipole signals.

FIGS. 8A-8D show a series of plots generated using the signal processingsystem of FIG. 7A in which the dotted signals have been low passfiltered.

FIG. 9A is a plot showing angular difference S between the directions ofactivation (a-hat) and greatest peak-peak voltage (m-hat) adjacent aplot of respiration over time as shown in FIG. 9B.

FIGS. 10A-10C are plots showing unipoles (FIG. 10A) Em (FIG. 10B), andE_(m⊥) (FIG. 10C) from a study with sinus rhythm (SR) and atrialfibrillation (AF).

FIG. 10D is a plot of bipolar EGM signals from a sample AF beat resolvedalong the dominant (m-hat) and non-dominant (m-hat-perp) directions.

FIG. 11A is a user interface component that includes a guide userinterface having a grid array of thirty-six user selectable triangularcliques suitable for triggering waveform display in response to eachclique selected.

FIG. 11B is a user interface component that includes a guide userinterface having a grid array of nine user selectable square cliquessuitable for triggering waveform display in response to each cliqueselected.

FIGS. 12A-12F are user interface components that include a guide userinterface and waveforms displayed in response to the user selection ofvarious combinations of square and triangular cliques.

FIG. 13 is a user interface component that includes a color map-basedguide to help locate ablation gaps using a peak-to-peak voltage (Vpp)map metric.

FIG. 14 is a schematic diagram of a user interface that illustrates theeffect changes in catheter orientation angle have on omnipolar voltagemeasurements.

FIG. 15 is user interface display that includes a floating guideinterface and an electric field loop interface displayed as an overlayand a m-hat directional element relative to a three-dimensionalgeometric surface model (GSM) and signal display such as displayedbipoles on a guide interface and a triggered map point acquisitionwindow.

FIG. 16 is a user interface display that shows maximal bipole directionsand activation regions using a color map for timing and m-hatdirectional elements.

FIG. 17 is data representation diagram that includes two panels (A andB) of vector fields for sinus rhythm (SR) and atrial fibrillation (AF)respectively, and a third panel that includes entropy values over tenheart cycles during SR and AF cycles.

FIG. 18 is data representation diagram for three AF cycles that shows avector field representation, a coherence grid derived from vectororientation, an adjusted indicia coded Vmax representation and arepresentation of populated Vmax values selected based on coherentvectors.

DETAILED DESCRIPTION Overview

The disclosure relates generally to applications of OrientationIndependent Sensing (OIS) and Omnipolar mapping Technology (OT) tovarious system, device, and method embodiments such as voltage mappingand others as recited herein. Voltage mapping is an important clinicaltool to evaluate arrhythmogenic myocardium and guides further diagnosticand therapeutic procedures. In part, the disclosure provides newanalytical tools and data representations based on OIS technology toenhance voltage mapping and other methods. Additionally, systems andmethods suitable for supporting OIS and OT systems and methods aredisclosed.

Further, OIS and OT implementations that provide end user interfaces,diagnostic indicia and visual displays generated, in part, based onmeasured data or derived from measured data are also disclosed. Ingeneral, the disclosure relates to implementations and features thatgenerate, collect, and process electrophysiological information (each ofthe terms “electrophysiology” and “electrophysiological” willhereinafter be referred to as “EP”). Similarly, the terms “OIS” and “OT”are used interchangeably herein unless otherwise specified.

Embodiments disclosed herein also apply optimization techniques todetermine the greatest voltage difference (or a relative extremum ofdifferential magnitudes/values thereof) of a local electric fieldassociated with an electrode-based diagnostic procedure and a vectorrepresentation thereof which is introduced in more detail below as{circumflex over (m)} (or m-hat) along with variations and extensionsthereof to other diagnostic vectors such as other OT metrics andparameters. Such a vector representation and other vectors derived fromand correlated with are also described herein and are generally referredto as diagnostic vectors. The diagnostic vectors can provide directionaland positional feedback as well as other visual indicia to an end user.For example, a display of such diagnostic vectors can be used to guidean end user manipulating a catheter to a location of interest such as aregion of tissue activation in the heart.

In addition, the disclosure also includes embodiments suitable forgenerating a reference trigger that reduces one or more error typesincluding directional effects and common mode far-field noise. Thereference trigger remains directionally independent even if determinedusing bipoles. The implementation of a directionally independentreference trigger can result in increased reliability and consistency.The foregoing and other embodiments and design features of varioussystems, methods, and devices are described herein. Prior to consideringthese in more detail, it is informative to consider how they relate tovarious OIS and OT implementations.

OIS describes one or more sensing methods including methods ofdetermining myocardial activation direction that is insensitive tocatheter orientation. Currently, myocardial activation is measured bytraditional bipoles created from neighboring electrodes, which span alimited number of directions due to the limited number and spacing ofphysical electrodes. By combining the information from all signals of aclique (collection of immediately adjacent electrodes used to derive EPcharacteristics) as an omnipole, an ‘effective bipole’ can becalculated. This combination avoids the limitation on direction imposedby physical bipoles.

Further, the ability to calculate a bipole in any direction allows forthe determination of the largest peak-peak voltage value regardless ofcatheter (bipole) orientation. Previously, orienting bipoles in thedirection of the E-field was required to yield the largest peak-peakvoltage, and was not possible to achieve in most circumstances. As aresult, the features described herein with regard to OIS, m-hat, andothers offer clear improvements relative to established methods.

Cardiac EP mapping today primarily uses electrograms (EGMs). The EGMsare typically bipolar and obtained from electrode pairs. Unipolar EGMsmay contain far-field information and less stable baselines that makethem less attractive for mapping purposes. A feature of the unipolarsignal that makes it useful for mapping is the fact that its morphologyand amplitude are independent of catheter orientation. Amplitudes andmorphology of bipolar EGMs are dependent on the wave front and relativeorientation of the electrode pair from which they are calculated andhence depend on the orientation of the catheter.

EP information may also be elicited by pacing a tissue or organ andobserving the resulting spread of depolarization from immediatelyadjacent to the site where capture occurs. These observations aredifficult with current technology because of pacing artifacts and othererrors but directional information in the form of or derived fromvoltage or electric filed information, as described herein, can be usedto reduce errors or remove degrees of uncertainty or ambiguity. Forexample, vectors or paths indicative of direction of activation or adirection opposite the direction of activation can advantageously beused as part of a user interface to facilitate positioning of adiagnostic electrode-based catheter.

A guide diagram or interface such as a color map or other user interfaceoverlay or component can be used as a diagnostic tool to guide targetedablation, data collection, and other procedures can be initiated oncethe catheter has been positioned relative to its target location. Agiven color map can also be referred to an indicia map or a map ormapping generally. A given color map can be represented as an indiciamap with hatching, shading, dotted and patterned lines, and other visualcues to provide a user with a visual awareness of the features of anysuch map. The use of a schema or rubric to define the spatialrelationship between electrodes in a catheter can be shown alone or withuseful indicia and a legend to guide an end user. Further, such arepresentation of electrodes can be used to visualize and measure theorientation and patterns of vectors in a vector field. With such vectorsbeing derived using EP measurements and the extremal vector techniquesdescribed herein, details relating to spatial coherence of such vectorsas determined by entropy-based analysis can be advantageously usedduring AF as discussed in more detail herein.

In addition, directional ambiguity in terms of how to decide where toposition a catheter to accurately target a specific region of activationcan be advantageously reduced or constrained or guided using m-hat,color maps, user interface indicia and other information when presentedto a catheter operator. The guiding of an end user and therepresentation of m-hat and other user interface features can bepresented in one or more user interface windows as described in moredetail below. For example, end user guidance can be provided byoutputting m-hat or other indicia relative to one or more views of ageometric surface model generated using EP measurements and/or EGMs.

With respect to bipoles, the dependence on orientation results ininconsistently measured amplitudes and morphology-based measurementslike activation times as a result of directional and other errors. Inturn, the errors also impact derived quantities like scar boundaries,activation direction, and conduction velocity. Generally, these types ofunwanted effects and error propagation between analytic modules thatrely on previously measured or generated data are generally referred toas errors or error types.

Given the unwanted effects associated with orientation anddirectionality issues, directionality-based errors is used as a categoryto reference these errors types and others. In part, the use of m-hat,direction independent reference triggers and other features disclosedherein support methods of reducing various error types.

In one embodiment, the methods, systems, and devices disclosed hereinmay be used without a navigational system and thus have wideapplicability in EP recording systems adapted for OT catheters. Further,determining a scalar E-field or voltage EGM signals can be performedstrictly within the catheter coordinate frame. The resulting scalarsignals and peak to peak levels do not need navigation (electrodeposition) information.

In addition, the foregoing overview of various embodiments can also becombined with or otherwise form part of a system or method to performone or more of the following: identifying ablation line gaps; map scarborders such as ventricular tachycardia (VT) scar borders; identify lowvoltage channels, and isthmus within a scar; assessing an atrialsubstrate; and locating reentrant entrance or exit sites. With theforegoing to provide context and outline of some of the embodiments tofollow, it useful to consider some system embodiments and catheterrelated features to provide further context.

Exemplary System Features and Embodiment Details

FIG. 1A illustrates one embodiment of a system 160 for mapping EPinformation corresponding to an anatomic structure onto amulti-dimensional (e.g., three-dimensional) geometry surface model (GSM)of the anatomic structure. The system 160 comprises, among othercomponents, a medical device 162 and a data collection and analysissystems 164 suitable for collecting EP data and other data as describedherein from a subject and to generate outputs that include datadisplays, user interfaces, and other OT related features disclosedherein. In one embodiment, the medical device 162 comprises a catheter,and system 164 comprises, in part, a processing apparatus 166.

The processing apparatus 166 may include one or more apparatus, devices,and machines for processing data, signals and information, including byway of example a programmable processor, a computing device such as acomputer, or multiple processors or computers. The apparatus caninclude, in addition to hardware, code that creates an executionenvironment for the computer program in question, e.g., code thatconstitutes processor firmware, a stack, a data management system, anoperating system, one or more user interface systems, or a combinationof one or more of them.

Further, the processing apparatus 166 can include machine readablemedium or other memory that includes one or more software modules fordisplaying a graphical user interface such as an interface for system160. The processing apparatus 166 can exchange data such as monitoringdata or other data using a network, which can include one, or morewired, optical, wireless or other data exchange connections.

The processing apparatus 166 may include a server computer, a clientuser computer, a control system, a diagnostic system such as, forexample, a cardiac diagnostic system, a microprocessor or any devicecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that processing apparatus 166Further, the term “processing apparatus” shall also be taken to includeany collection of computing devices that individually or jointly executea set (or multiple sets) of instructions to perform any one or more ofthe software features or methods or operates as one of the systemcomponents described herein.

The processing apparatus 166 may take the form of an electronic controlunit, for example, that is configured to obtain a GSM of the cardiacstructure, and to construct an EP map corresponding to the cardiacstructure using data collected by, for example, the catheter 162. Thecatheter 162 is configured to be inserted into a patient's body 168, andmore particularly, into the patient's heart 170. The catheter 162 mayinclude a cable connector or interface 172, a handle 174, a shaft 176having a proximal end 178 and a distal end 180 and one or more sensors182 (e.g., 182 ₁, 182 ₂, 182 ₃) mounted in or on the shaft 176 of thecatheter 162. In one embodiment, the sensors 182 are disposed at or nearthe distal end 180 of the shaft 176. The connector 172 providesmechanical, fluid, and electrical connection(s) for cables, such as, forexample, cables 184, 186 extending to system.

The sensors 182 mounted in or on the shaft 176 of the catheter 162 areelectrically connected to system 164, and the processing apparatus 166thereof, in particular. The sensors 182 may be provided for a variety ofdiagnostic and therapeutic purposes including, for example and withoutlimitation, EP studies, pacing, cardiac mapping, and ablation. In anembodiment, one or more of the sensors 182 are provided to perform alocation or position sensing function such as guidance relative to oneor more activation regions wherein activation can occur at differentpoints in time.

Accordingly, in such an embodiment, as the catheter 162 is moved along asurface of the cardiac structure and/or about the interior thereof, thesensor(s) 182 can be used along with the display outputs and vectors orline segments described in more detail with m-hat and its associatedcohort of other diagnostic vectors and OT metrics, operators andparameters.

In one embodiment, system 164, and the processing apparatus 166 thereof,in particular, is configured to obtain a GSM of the cardiac surface (orat least a portion thereof), and to map EP information corresponding tothat cardiac structure onto the GSM. Examples of GSMs are shown in thegraphical user interface representations in FIGS. 13, 15, and 16 whichare discussed in more detail herein. The processing apparatus 166 isconfigured to use, at least in part, data (location data and/or EPdata/information) collected by the catheter 162 in the construction ofone or both of a GSM and an EP map and to other perform the various OTrelated mapping and other methods and features disclosed herein.

In an embodiment, wherein system 164 is configured to construct the GSM,system 164 is configured to acquire location data points collected bythe sensor(s) 182 corresponding to the cardiac structure. System 164 isconfigured to then use those location data points in the construction ofthe GSM of the cardiac structure. System 164 is configured to constructa GSM based on some or all of the collected location data points. System164 is configured to function with the sensor(s) 182 to collect locationdata points to support the directionally independent voltage mapping andother data analysis and user interface features disclosed herein. Insuch an embodiment, system 164 may comprise an electric field-basedsystem, such as, for example, the EnSite NavX™ system commerciallyavailable from St. Jude Medical, Inc., and generally shown withreference to U.S. Pat. No. 7,263,397 entitled “Method and Apparatus forCatheter Navigation and Location and Mapping in the Heart”, the entiredisclosure of which is incorporated herein by reference. Anotherexemplary system 164 is the EnSite Precision™ system, which uses bothimpedance-based and magnetic based localization.

As part of the user interface designs and other analysis and dataprocessing and display features disclosed herein, the GSM representationis depicted relative to one or more line segments, scalar values, orvectors. These geometric, directional, scalar values, alone or incombination are designed to be indicative of a direction of heart tissueactivation or otherwise inform the user of a path or direction ofmovement to iteratively test via catheter rotation and positionalchanges to reach of target position of interest.

With reference to FIG. 1B, in addition to the processing apparatus 166,system 164 may include, among other possible components, a plurality ofpatch electrodes 188, a multiplex switch 190, a signal generator 192,and a display device 194. In another exemplary embodiment, some or allof these components are separate and distinct from system 164 but thatare electrically connected to, and configured for communication with,system 164.

The processing apparatus 166 may comprise a programmable microprocessoror microcontroller, or may comprise an application specific integratedcircuit (ASIC). The processing apparatus 166 may include a centralprocessing unit (CPU) and an input/output (I/O) interface through whichthe processing apparatus 166 may receive a plurality of input signalsincluding, for example, signals generated by patch electrodes 188 andthe sensor(s) 182, and generate a plurality of output signals including,for example, those used to control and/or provide data to, for example,the display device 194 and the switch 190.

The processing apparatus 166, such as for example through memory 197,includes or accesses one or more software modules or programs 199 a, 199b, and 199 c, such as a reference trigger generation or processingmodule, an optimization module suitable to select max, min, and relativeextremum values from electric field and potential values, an m-hatdetermination module, vector operation modules, GSM display modules,m-hat display modules, user catheter guidance modules, activation regiondisplay modules, user interface modules, voltage mapping modules andother software modules. The modules 199 a, 199 b, and 199 c can besubsets of each other and arranged and connected through various inputs,outputs, and data classes. Also, three exemplary modules 199 a, 199 b,and 199 c are depicted in FIG. 1A, any suitable number of modules can beinstalled or access by system 160 various embodiments.

The processing apparatus 166 may be configured to perform variousfunctions, such as those described in greater detail above and below,with appropriate programming instructions or code (i.e., software 199 a,199 b, and 199 c). Accordingly, the processing apparatus 166 isprogrammed with one or more computer programs encoded on a computerstorage medium for performing the functionality described herein. Thesefunctions can include generating one or more user interface (UI)components suitable for display on the display device. The userinterface components can also be displayed on the user input device tothe extent it includes a touch screen or other display. One or more ofthe software modules or components thereof can be used to implement theuser interface components described and depicted herein. Theseinterfaces can include a select all feature (SA) by which all the squareelectrodes or all of the triangular electrodes in an array can beselected for displaying EP signals and related parameters relativethereto.

With the exception of the reference patch electrode 188B called a “bellypatch,” the patch electrodes 188 are provided to generate electricalsignals used, for example, in determining the position and orientationof the catheter 162. In one embodiment, the patch electrodes 188 areplaced orthogonally on the surface of the body 168 and are used tocreate axes-specific electric fields within the body 168.

In one embodiment, the sensor(s) 182 of the catheter 162 areelectrically coupled to the processing apparatus 166 and are configuredto serve a position sensing function. More particularly, the sensor(s)182 are placed within electric fields created in the body 168 (e.g.,within the heart) by exciting the patch electrodes 188.

In part, the disclosure uses electrodes on diagnostic catheters toderive local “pseudo bipolar”, “equivalent bipole”, directionindependent reference signals, diagnostic vectors, or “omnipolar”signals that are catheter orientation independent and are free oflow-frequency noise and far-field effects. The electrodes can be locatedon a diagnostic or other catheter or in some embodiments can be locatedon multiple catheters where electrodes on the catheters are located nearor adjacent each other. Furthermore, the equivalent bipolar EGMs soderived possess characteristic shapes and relationships that reflectphysiologic and anatomic directions which enable better contact maps byvirtue of more consistent activation timing directions.

FIG. 2A shows an embodiment of a diagnostic catheter that can be usedfor mapping and data collection applications as described herein.Various diagnostic catheters that include an array of electrodes orother electrode configurations can be used to implement the embodimentsdisclosed herein. In one embodiment, the diagnostic catheter is a highdensity (HD) catheter such as an HD grid catheter. The Advisor™ HD GridMapping Catheter (commercially available from St. Jude Medical, Inc.) isan exemplary HD catheter suitable for use in various embodiments.Similarly another embodiment includes an ablation catheter withsegmented electrodes with a distal ablating electrode with proximalsegmentation or vice versa enabling tetrahedral or multiple triangularclique formations.

Examples of other types of ablation and/or diagnostic catheters that canbe used for collecting data as described herein are disclosed in U.S.Patent Publication No. 2016/0045133 entitled “Utilization of ElectrodeSpatial Arrangements for Characterizing Cardiac Conduction Conditions,”the contents of which are incorporated herein by reference in theirentirety. Generally, any suitable diagnostic catheter can be used asapplicable with any given embodiment disclosed herein.

FIG. 2A illustrates one embodiment of a diagnostic catheter 10comprising a catheter body 11 coupled to a paddle 12. The catheter body11 can further comprise a first body electrode 13 and a second bodyelectrode 14. The paddle 12 can comprise a first spline 16, a secondspline 17, a third spline 18, and a fourth spline 19 that are coupled tothe catheter body 11 by a proximal coupler 15 and coupled to each otherby a distal connector 21 at a distal end of the paddle 22. In oneembodiment, the first spline 16 and the fourth spline 19 can be onecontinuous segment and the second spline 17 and the third spline 18 canbe another continuous segment.

In other embodiments, the various splines can be separate segmentscoupled to each other. The plurality of splines can further comprise avarying number of electrodes 20. The electrodes in the illustratedembodiment can comprise ring electrodes evenly spaced along the splines.In other embodiments, the electrodes can be evenly or unevenly spacedand the electrodes can comprise point or other types of electrodes.

In FIG. 2A, a representative group of catheter electrodes A, B, C, D, E,F, and G are depicted with regard to an exemplary catheter 10. Thecentral clique of electrodes 215 includes electrodes A, B, C, and D. Inone embodiment, the central clique defines a square with each vertexcorresponding to one of A, B, C, and D as shown by the dotted lines forcentral clique 215. Although applicable to other four electrodegroupings, the four electrode square (or rectangle) clique defined by A,B, C, and D can also be analyzed by deconstructing the ABCD groupinginto four triangular electrode cliques. With regard to FIG. 2A, the fourtriangular electrode groupings or cliques of center clique 215 asdefined by their vertices are ABD, ACD, CAB, and CDB. In this way, thereare four triangular electrode groupings one for each of the fourvertices of the square.

Each vertex forms a right angle with two orthogonal sides of the squareor rectangular clique for four electrodes. As shown, by the dottedlines, an exemplary triangular grouping is also shown by electrodes GHAto the left of central clique 215. Measurements obtained from thevarious electrodes can be used to determine various parameters ofinterest such as Emax or Vmax. The E field trajectory over adepolarization typically forms a loop, which can be shown in a two orthree-dimensional graph such as those shown in FIGS. 3, 14, and 15. Efield derived loops, such as for example those derived using a leastsquares approach, preferably merge information from all possible bipolesof a clique. Generally, when determining Emax (or Vmax), the determinedvalues will exceed the amplitudes of individual constituent bipoles.This relationship between the amplitudes of their respective constituentbipoles is true with respect to measurements using triangular cliques asdiscussed below.

Still referring to FIG. 2A, and the central clique formed by electrodesA, B, C, and D, in light of the discussion of omnipoles above, it isuseful to consider the electrode cliques with regard to bipoles. Thereare six possible bipoles, four from the sides of the square (e.g. A-B,C-D, A-C, and B-D) and two diagonals (e.g. A-D and C-B). In general, inthe context of using a mapping system (such as, for example, an Ensite™Velocity mapping system) to assess voltages from a single or rectangularsquare clique, the foregoing six bipoles would be present for each groupof four electrodes.

To provide further context, although depicting a different diagnosticelectrode-based catheter, in FIG. 2B, an idealized catheter coordinateframe that includes axes for the +x and +y directions, respectively.These reference frame axes for bipole direction is also shown in FIG.2A. The clique of four electrodes A-D is shown for a subset of acatheter's electrodes to provide information relating to bipoles. Inparticular, the bipole potential equations and directionality of V_(x)and V_(y) are displayed. These equations can be written in the followingform:

$V_{x} = \frac{( {V_{A} - V_{B}} ) + ( {V_{C} - V_{D}} )}{2}$$V_{y} = {\frac{1}{2}\lbrack {( {V_{A} - V_{C}} ) + ( {V_{B} - V_{D}} )} \rbrack}$

Methods of determining E_(max) (or equivalently Vmax) are expected toyield from E field loops voltage values which are equal to or greaterthan those of the bipoles making up a clique. However, this is strictlytrue only for triangular cliques. For square cliques there is anaveraging effect of opposing side bipoles as seen in the equations forV_(x) and V_(y) above and in FIG. 2B. Under certain scenarios, E_(max)is constrained to be greater than or equal to the peak-to-peak E fieldsof the two adjacent sides and their diagonal. For example, the foregoingE_(max) constraint applies to isosceles right triangular cliques andleast squares solutions to E(t). When expressed as a maximal bipolevoltage, V_(max) will also be greater than or equal to its constituentside bipoles as well as the scaled for excess length voltage of theconstituent diagonal.

In light of the various diagnostic features and embodiments disclosedherein, it is also informative to consider methods of enhancing spatialresolution in the context of electrode cliques. If a single bipole wereto be substantially greater in peak-to-peak voltage than any of itsneighboring bipoles, then the four electrode square clique approachwould map this with mid-level values as mentioned above to each of thetwo adjacent squares. If instead, the triangular clique method is used,this same large single bipole voltage would be mapped exactly to fourlarge values belonging to the triangular cliques that are just 1 mm eachside of the bipole. As a result, the triangular clique approachfaithfully provides the single bipole's high value while achievinggreater spatial resolution by mapping that high value to a region ofhalf the surface area located precisely on both sides of his largebipole.

From this example, dividing the catheter electrode groupings such thatan array of triangles is defined provides a method to increasegranularity and signal resolution. The benefits of such an approach havebeen empirically validated and shown to improve spatial resolution.Specifically, the use of triangular cliques yields an improved spatialresolution to relative to the use of square cliques with regard toapplications disclosed herein. In one embodiment, as shown in FIG. 12Bdiscussed in more detail herein, groups of triangles in the array definerepeating square groupings that are rotated 45 degrees or another angleof rotation relative to the square clicks of the catheter.

Although the diagonal bipoles have longer interelectrode spacings, andlonger spacings generally imply greater voltages, they are not alwayslarger than any of the sides. Decomposing an OT square clique into fourmaximal bipole (omnipole) voltage values and outputting them as part ofa user interface display as four triangular omnipole voltages with eachnext to its bipole constituents is an embodiment of the disclosure. Nowin each of these four cases, the omnipole peak-to-peak value will meetor exceed the greatest constituent bipole. This decomposing and displayapproach is in contrast to showing one square omnipole next to its sixconstituent bipoles.

In one embodiment, according to one method or system implementation, twobipole waveforms and the corresponding omnipole “maximal bipole” voltagewaveform are displayed using one or more user interfaces. Accordingly,in one embodiment, in which a triangular array-based approach isimplemented, instead of obtaining nine voltage values (centered in eachof the nine squares that result from a diagnostic catheter having a 4×4array of electrodes) at 4 mm spacings with respect to each other, 36 OTvoltage values are obtained in an array, but with only 2 mminterelectrode spacings. The spatial resolution of voltage maps therebyimproves over the 4 mm square clique approach. Further, undesirablevoltage reductions are avoided when bipole orientations do not alignwith activation directions. This latter problem contributes to thegeneration of splotchy voltage maps. As a result, the use of an array oftriangular cliques to address such noise and resolution related issues,is desirable.

OIS and OT based technology provide for voltage mapping methods, systemsand devices. As discussed with regard to FIGS. 3 and 4, wave propagationmodels and electric field loop analysis allows for various OT metricsand applications thereof to be generated. These metrics and otherrelated tools and information can extend existing techniques based onEGM signal analysis and monitoring. For example, among measures for EGMsignal amplitude, the most commonly used is peak-to-peak voltage (PP orV_(pp)). With the advent of OT friendly catheters such as HD Grid, newmeasures of local tissue can be derived such as the direction of themaximal bipole voltage or the EGM signal perpendicular to thatdirection. The extensions in the form of operators, parameters, vectors,and associated user interface components and reference signals offeradvantages relative to existing EP measurements and data analysis. Toprovide context, additional disclosure follows to establish various OTmetrics and related data and applications with regard to FIG. 3 and FIG.4.

FIG. 3 is a graph of an E(t) loop in three-dimensions. With eachdepolarization, the local electric field vector, E, sweeps out a looplike trajectory governed by anatomic and physiologic factors adjacent tothese arrangements of electrodes. Two dimensional electrode arrangementsallow the resolution of Et, the “tangent bipole vector”, to which wavepropagation principles can be applied and can be used to introduce ascalar version of Et along the unit activation direction â and identifythis electrogram signal as Ea (not shown).

As part of the analysis of the E-loop data, it is useful to focus on theportions of a given E-loop that contain the most information. Theseinformationally dense parts of the loop correspond to portions of theloop in which spacing between the adjacent electric field data pointvalues in the loop is largest. These times or data points correspond towhen the E-field changes most rapidly. Accordingly, it is at these timeor data points that are least influenced by various error types such asnoise, artifacts and other unwanted effects. In light of the foregoing,it is advantageous to develop a diagnostic and error reducing mechanismto extract the most useful information from collected electrogram dataand other EP data.

The desire to find the times, unit direction vector, and E-field “span”associated with when the magnitude of the vector E(t_(j))−E(t_(i)) isgreatest are all items of interest that can be incorporated in the OTmetrics described herein. The span across the whole loop (not justintervals where it changes greatly) includes the curve segment betweenendpoints A and B is of interest in various embodiments. This span isthe 2-D or 3-D equivalent of peak-to-peak for a 1-D signal vs. time. Inpart, the disclosure generalizes peak-to-peak voltage (the most commonway to assess amplitude in clinical EP) through using E field orequivalently voltage loops. Further, in one embodiment, it is desirableto maximize the magnitude of the vector E(t_(j))-E(t_(i)) as part ofdetermining one or more OT metrics.

In light of the foregoing, a family of OT metrics, which can includevarious diagnostic vectors, can be defined that enhance data analysisand user interface display option by providing additional directionalinformation. To achieve this, a vector m-hat or {circumflex over (m)}can be defined as a unit vector or a non-unit vector. In one embodiment,the unit direction vector m-hat from the loop signal is generated usingthe following relationship:

$\hat{m} = \frac{{E( t_{j} )} - {E( t_{i} )}}{{{E( t_{j} )} - {E( t_{i} )}}}$

and where t_(i) and t_(j) have been chosen to maximize|E(t_(j))−E(t_(i))| and t_(j)>t_(i) wherein bold denotes a vectorquantity.

As shown in FIG. 3, m-hat is oriented in the direction of maximum (arelative extremum) peak-peak voltage. E_(m)(t) is the signal E(t)projected onto {circumflex over (m)} (Em(t)=E(t)·{circumflex over (m)}).This can also be written as E_(m)(t)=<{circumflex over (m)},E(t)>, wherethe inner or dot product of two vector quantities a and b is <a, b>. Inone embodiment, E_(m)(t) is another example diagnostic vector.

As defined above by the order of t_(i) and t_(j) the vector {circumflexover (m)} has a defined direction. This direction however is arbitrary,ambiguous to ±180°. Unit direction vector a-hat represents a bestestimate of activation direction based on phi-dot and Ea. M-hat providesinformation about the axis of propagation distinct from activationdirection â and potentially more reflective of tissue properties. M-hatis independent of physical electrode orientation.

In one embodiment, other OT metrics in addition to m-hat can begenerated. As noted above, it is possible to generate Em(t) byprojecting the E-field onto m-hat. Vm(t) may then be found byVm(t)=Em(t)*Electrode Spacing. This scalar voltage signal isproportional to Em(t) but in more familiar units (mV). Both of thesesignals are independent of catheter orientation. Vm(t) contains thelargest peak-peak voltage for a depolarization (referenced tointerelectrode spacing), in cardiac or other tissue which can be used todetermine meaningful and robust characterization of local tissueproperties.

A general method to generate m-hat using a reference signal as generatedusing the system of FIG. 7A is shown in FIG. 5. In one embodiment, themethod includes obtaining EGM unipolar and bipolar signals (Step 100).Given these signals, which are typically stored in one or moreelectronic memory devices, processing of the signals occurs. In oneembodiment, processing the unipolar and bipolar signals is performed toobtain the vector V(t) from its orthogonal components (V_(x)(t),V_(y)(t)) along the catheter's x axis and y axis (Step 105). Areference trigger can be determined generally or using one of thespecific approaches described herein (Step 110). The reference triggeris used to define a window for searching for voltage values.

Accordingly, the method may include searching V(t) over a defined windowfor the maximum voltage difference or relative extremum thereof, whichis identified as Vm_Vpp. (Step 115) After the search to determineVm_Vpp, the axis of this maximal span is generated as the unit vector mor m-hat. (Step 120). Further, once the unit vector m has beengenerated, V(t) can be projected onto m to obtain the maximal bipolesignal Vm(t) (Step 130).

The perpendicular direction to vector m-hat, m-hat-perp, can also begenerated by vector operations. m-hat-perp, in turn, as another OTmetric can be used to determine smaller peak-peak voltages that may bemeaningful in defining late potentials or fractionation, by attenuatinglarge dominant direction signals or other properties. Contrastingvoltage measurements obtained by projecting E(t) or V(t) onto m-hat andm-hat-perp can provide information about local tissue properties.Em_perp(t) and Vm_perp(t) can be generated from m-hat-perp, and used toassess data sets to detect or evaluate conduction, complexity, andarrhythmogenicity related signals. The foregoing vectors are examples ofdiagnostic vectors suitable for operating upon various other vectors andfunctions.

M-hat is unique from activation direction a-hat, and together theiragreement can serve as a quality measure. Discrepancies between the twomay be indicative of pathology that can initiate or sustain anarrhythmia. This feature is shown in FIG. 4 by the angular deviationmeasure S.

FIG. 4 illustrates the unit activation direction vector 91, wavecrestvector 92, surface normal vector 94, wavefront crest 90, and conductionvelocity vector 93. M-hat is typically aligned with the unit activationvector 91. To the extent it deviates from activation 91 by an angledeviation S, the amount of deviation of S can serve as a threshold fordiagnostic purposes. A single depolarization wavefront 90 is depictedbased on a unipolar traveling wave voltage signal, φ(x,y,z,t).Propagation of the depolarization wavefront 90 occurs from left to rightin the view. The catheter orientation independent omnipole signals Enand Ea possess characteristic shapes and amplitudes in normalmyocardium.

In addition to angular deviations and directional trends, m-hat can beused to generate other OT (signals and) metrics. In turn, such metricscan be used for subsequent data analysis. For example, the inherentseparation of Em_perp(t) from E(t) as a non-dominant signal allowssignals from fibrosed and irregular conduction pathways to bediscernable relative to healthier tissue signals. As a result, abnormalearly or late potentials may be more clearly visualized. Accordingly, byincluding Em(t) and Em_perp(t) as OT metrics in conjunction with theothers described herein it may be possible to more accurately recognizetrue far field signals.

In the absence of a navigational system (such as NavX), the abovemetrics may be obtained and visualized in an EP recording system fromideal electrode positions to acquire results similar to the 3D full(NavX coordinate) calculation. Typically, the results will be morerobust to NavX distortions.

Where navigational and/or 3D mapping systems are available, the OTmetrics (including m-hat, m-hat-perp) can benefit by being portrayedwith respect to the cardiac anatomy. M-hat and m-hat-perp can betransformed from an ideal catheter coordinate system to a 3Dnavigational coordinate system where additional value is derived fromanatomic context such as can be seen for example in FIG. 16 (discussedin more detail below).

In the 2D case, it is straightforward to obtain a second unit directionvector m-hat⊥ (also ambiguous to ±180°) which is perpendicular to m-hat.In the 3D case, both m-hat and a vector normal to the plane of theclique's electrodes, n-hat, are operated upon to derive m-hat⊥. Thescalar E or V EGM signals perpendicular to m-hat can be determined usinga unit vector and the appropriate reference electrode spacing. The unitvector is m-hat⊥, {circumflex over (m)}_(⊥).

E _(m⊥)(t)=<{circumflex over (m)} _(⊥) ,E(t)> and V _(m⊥)(t)=E_(m⊥)(t)·Reference Spacing,

wherein the Reference Spacing refers to the center-to-centerinter-electrode distance (e.g., 4 mm for the Advisor™ HD Grid MappingCatheter). E_(max⊥) and Vmax⊥ are peak-peak values of Em⊥(t) and Vm⊥(t).These signals may be more sensitive and specific for fractionation andLAVA/late potentials which are ablation targets because the largersignals occur along a perpendicular direction.

Differences between m-hat and a-hat directions (0-90° since polarity ofm-hat is arbitrary) have been observed in certain disorganizedpropagation conditions. As mentioned above, they tend to be closelyaligned for propagation in homogeneous tissue. Accordingly, adiscrepancy between them may be indicative of pathology that caninitiate or sustain an arrhythmia. One implementation is to make thisassessment at a particular location for just a single beat and a singleclique of adjacent electrodes.

A more reliable assessment for that location could result fromobservations over time (a few successive beats). A mean or medianangular discrepancy of say >15° might indicate underlying EP complexityand arrhythmogenicity, while <10° indicates a regular simple rhythm (SR,Flutter, etc).

In terms of detecting or correlating catheter-measured EP data with anevent, a state of a subject under test, or another parameter variousmetrics can be considered such as angle deviations, loop eccentricitiesand others. In one embodiment, such a method includes determining one ormore directional deviations between {circumflex over (m)} and â. Inturn, it is then possible to generate an alert when the one or moredirectional deviations exceed a threshold. An alert gives an end usernotice and permits enhance diagnostic review and additional testing.

In one embodiment, the threshold used to evaluate angular deviations S(see FIG. 4) relative to {circumflex over (m)} and â is based on thevariations in healthy tissue when catheters are held in the same spot.Based on experiments and trials, 95% of angular deviations between a-hatand m-hat in this condition lie within a range of about 15 degrees orless. In one embodiment deviations of angular distances S that rangefrom about 15 degrees to about 20 degrees or more can be used to set athreshold for abnormal tissue characteristics and potentially indicativeof arrhythmogenic tissue.

In one embodiment, S values that range from about 15 degrees to about 20degrees or S values greater than about 15 degrees can be used as athreshold to perform tissue ablation, perform further diagnosticanalysis to assess procedure selection, or generate an on-screen alertfor the end user to give them notice of the relevant threshold being metor exceeded. Further reliability of one or more measurements or outputsto an end user can also be increased within a single beat by makingangular discrepancy observations over nearby or all catheter cliques,using a similar threshold for complexity and arrhythmogenicity.

FIG. 6 is a schematic illustrating electrode location andrepresentations of m-hat in the context of coordinate system changes ofa diagnostic catheter. An HD Grid catheter displayed in SJM's EnSitePrecision™ cardiac mapping system is shown on the left. The centralsquare clique having electrode vertices ABCD is shown on the catheterswhich have splines P1-P4. Six downward pointing arrows are shown in a 3by 3 arrangement. These arrows represent the m-hat vector direction, orthe 3D direction of maximal bipoles in the context of patient anatomy.On the right side of the FIG. 6, an idealized 2D representation of acatheter, also with six arrows representing the m-hat direction, isshown. This catheter coordinate frame (x and y axes, or x,y,z axes) doesnot require navigation-derived electrode coordinates. As a result, thesecatheters may function independent of NavX or with severe distortion.The catheter coordinate frame facilitates calculation of one or more ofthe OT metrics. It may then be transformed to the patient's anatomicalcoordinate frame using rigid body rotation and translation derived fromthe positions and orientations of the catheter's electrodes in bothcoordinate frames.

FIG. 7A is a block diagram of a signal generating system 30 suitable forgenerating a reference trigger signal. In one embodiment, the disclosureincludes a bipole-based but catheter orientation independent (OT)reference/trigger signal. The combined advantages of bipole rejection offar field signals and catheter orientation independence improvesreference signal accuracy. In one embodiment, the reference triggergeneration uses all possible clique bipoles to obtain in the 2D caseE(t)=(Ex, Ey)(t). From this functional relationship using such acollection of bipoles, a single signal that reflects the energy in allcomponent bipoles is generated. Although bipoles are used, thecalculation remains directionally independent. As a result, referencetriggers may be more consistently reliable than traditional methods.

Returning to FIG. 7A, the top right block of the diagram 301 depictsinput ECG information and a legacy approach of reference signalgeneration that uses all measured electrograms from unipolar signalblock 305 (without bipole involvement). All of the unipoles are routedby default from source 305 as part of a first step to selector block 325shown as step 2. At step 2 b, a selection of key bipole signalscorresponding to the central clique (such as clique ABCD discussed abovewith regard to FIGS. 2A and 2B)) are identified. Unipole electrograms 6,7, 10, and 11 identified in signal section block 320 and are selected atthe selector 325 for transmission onward. All of the other signals fromthe source block 305 are blocked and do not pass the selector 325.

Next, at matrix multiplier 333, the unipole signals and their associatedbipole signals are combined together with various weights to determineelectric field components along the catheter x-axis and y-axis. Theconstant C in output block of step 3B specifies the weightedcombinations. C may also contain the interelectrode spacing in analternative embodiment. As shown, however, two signals Ex and Ey areoutput to converter 340 and subsequently converted into voltage signalsV_(x) and V_(y).

In one embodiment, which is optional in some cases, the derivative ofthe V_(x) and V_(y) signals is obtained at derivative block 350. Next,the time derivatives of the V_(x) and V_(y) signals are transmitted tonormalization block 355. Within this block, the signals are operatedupon to normalize them to generate a Euclidean magnitude thatincorporates the directionality of the bipoles and the originalomnipoles. This output signal has the form of an omnidirectional energysignal. Next, normalization block 355 sends the omnidirectional signalto low pass filter block 363. Once filtered, the resultant signal thenenters a threshold crossing and detection block (block 375). Finally,several intermediate signals from the processing as well as the outputof block 375 are displayed on scope 345 for review by a user. Thisprovides an overview of the main processing steps.

To provide some additional detail of some of the processing blocks it isuseful to return to Block 375. After low pass filtering to smooth theenergy signal, the first local maximum above the noise floor is detectedfor the filtered signal at depolarization subsystem 375. A conventionalrefractory period is then in effect which is used to exclude falsemultiple depolarizations as part of this subsystem 375. In addition, anoise floor and/or a threshold detector can be used to further shape andextract meaningful signal data. In one embodiment, the thresholddetector is a zero-crossing detector. The offset evaluation block 377provides further optional signal shaping before the reference signal isgenerated as an output from block 375 or 377 and displayed on scope 345.The dotted reference signal is shown as dotted trace in FIG. 8D.

In one embodiment, the reference signal is generated using a selectedsubset of representative bipoles. The reference signal can come from(for HD Grid or other electrode-based catheter) the middle squareclique. Accordingly, its use can be extended and remains relevant to allsurrounding cliques of any type. Alternatively it may come from a userselected clique that is used for all catheter cliques. Finally, it maycome from each clique, making detection independent. This would be mostuseful for situations when the catheter is placed over a line of blockwhere the depolarization times of clique signals from a single cathetercould be substantially different.

FIG. 7B shows an exemplary method for determining a directionindependent reference trigger with the benefits of using bipoles andomnipoles. In part, the method includes selecting a clique of nearbyelectrodes in a non collinear arrangement (Step A). Convertingcombinations of selected unipoles and/or associated bipoles to E-fieldcomponents along x catheter axis and y catheter axis is another step(Step B). The method can also include converting Ex and Ey electricfield components to voltage signals V_(x), V_(y) (Step C). NormalizingV_(x) and V_(y) signals to output a combination energy signal correlatedwith a Euclidean magnitude or energy magnitude is another step (Step D).The method can also include filtering the combined energy signal togenerate filtered output signal correlated with depolarization activity(Step E). The method can also include detecting depolarization activityin filtered output signals using refractory period, noise floor, andthreshold crossing approaches (Step F).

FIGS. 8A-8D show a series of plots generated using the signal processingsystem of FIG. 7A. FIG. 8A shows ECG traces synchronized in time to thesignals below in the other plots. FIG. 8B shows the V_(x), V_(y) signalsfrom FIG. 7A and the associated far field noise regions FF. FIG. 8Cshows the signal generated from normalizing the V_(x), V_(y) signals.The low pass filtered signal from FIG. 7A is shown with the dottedlines. The reference signal uses four unipole signals to create sixeffective bipoles, naturally reducing common mode and far-field noise asdiscussed above. The method may be supported by a combination of movingaverage filters, derivatives, and lowpass filters as referenced in FIGS.7A and 7B. In FIG. 8D, the dotted ticks or vertical spikes are generatedusing the steps of FIG. 7B or generated by the system of FIG. 7A. Thedotted reference signals in FIG. 8D are slightly delayed from the EGMsignals themselves as a result of the low pass filter's delay. Sincethis filter's group delay is known from its design, this can becompensated for to remove the delay.

FIG. 9A shows angular difference between the directions of activation(a-hat) and greatest peak-peak voltage (m-hat), which correspond to S asshown in FIG. 4. The two vector directions diverge from times 4-11seconds which correspond to AF beats. Times 0-4 and 4-32 secondscorrespond to sinus rhythm, which is shown in FIG. 9B. In addition toconsidering angular deviations, S, the eccentricity of electric fieldloops can also be evaluated using m-hat and other OT metrics disclosedherein.

To provide context for the use of eccentricity, it is useful to consideranother measure of eccentricity of the E-field or voltage loop by theratio E_(max⊥)/E_(max) which must always be ≤1. Very eccentric loopshave a ratio <0.4 and reflect a predominance of healthy conduction inhomogenous tissue. Round loops have ratios >0.6 and reflect complexityand possibly identify arrhythmogenic locations. In some embodiments,E_(min) has been found to be proportional to or substantially the sameas E_(max⊥). Accordingly, E_(min) may be used in lieu of or to otherwisereplace references to E_(max⊥) as described and depicted herein. E_(min)and E_(max) can also be described using the following relationships:

E _(min)=min_(θ){<[cos θ, sin θ],E _(loop)>}

E _(max)=max_(θ){<[cos θ, sin θ],E _(loop)>}

Eccentricity alone may be insufficient to characterize abnormal loopshapes. Loops may cross themselves or have significantly non-ellipsoidshapes. In these circumstances, the mismatch between loop area andcircumference may be employed as an index of complexity, and Green'stheorem may be applied to provide a polar-planimeter-related index.

FIGS. 10A-10C are plots showing unipoles (FIG. 10A) Em (FIG. 10B), andE_(m⊥) (FIG. 10C) from a study with sinus rhythm (SR) and atrialfibrillation (AF). The horizontal axis corresponds to time with units ofseconds. The vertical axis values for the three figures correspond tounipole voltage (in mV), Em, and Em_perp, respectively as shown. Theserepresentations can be provided using electric field or voltage values.If using Em and Em_perp, then the vertical axis units are mV/mm. Inturn, if using Vm and Vm_perp, then the vertical axis units are mV. Fora given beat and square clique, the 4 unipole signals make E_(x) andE_(y) omnipoles from which an E(t) loop is created (see FIG. 3) andE_(m)(t) and E_(m)⊥(t) can be identified. The first two beats are SR,while the last two are AF. The ratio of Em_perp/Em is 0.4 for beat 1 and0.83 for beat 4. This suggests that the E-field loop for beat 4 isnearly circular, or non-eccentric.

Another application of deriving two-dimensional electrogramcharacterizations at clique locations is that by separating dominantfrom nondominant (Em(t) and Vm(t) vs. Em⊥(t) and Vm⊥(t) respectively)signals, signals from fibrosed and irregular conduction pathways can bedetected rather than the case where they are obscured by nearbyhealthier tissue signals.

FIG. 10D is a plot of bipolar EGM signals from a sample AF beat resolvedalong the dominant (m-hat) and non-dominant (m-hat-perp) directions. Asshown, the non-dominant signal contains a greater number of smallersharp deflections, suggesting fractionation. Signals like this Em-perpmay indicate complex conduction patterns, fibrosis, or fractionationsuitable for ablation targeting.

M-hat derived metrics may be used to classify near-field and far-fieldsignals that do not rely entirely on basis of frequency (far-fields tendto be low frequency) or timing (one type of far field is coincident withQRS) but rather on level of orientation dependence. If small in alldirections (e.g. a small 2- or 3-D loop) EGM signal components are trulyfar field and one may safely ignore them, particularly for unipolederived signals or characteristics (e.g. phi-dot or unipolar V_(PP)).Upon identifying a unipolar signal that has little significant bipolaramplitude in any direction, it is useful to briefly blank or block thevisualization and use of any of its derived signals and characteristics.

A similar approach may be used for the traveling wave treatment of OT.OT's separation of dominant (activation) from nondominant (wavecrest)signals (Ea(t) and Va(t) vs. Ew(t) and Vw(t) respectively) signals canhelp identify difficult to discern signals. As an example, this wouldinclude signals from fibrosed and irregular conduction pathways. Asimilar method can be used to help these signals standout from nearbyhealthier tissue signals.

User Interface (UI) Features and Exemplary Embodiments

The various m-hat and associate family of diagnostic vectors, andcorrelated parameters and operators, which apply generally to the OT andOIS embodiments disclosed herein can be used to generate display elementand user interfaces. Such user interfaces and display elements caninclude maximal and minimal voltage values, maximal bipole signals, thedirections of maximal bipoles, and color map displays (generallyreferred to as OT metrics or parameters in on embodiment). All of theseand other vector and scalar data and signal can be displayed in variousforms as graphical user interface elements. These can include scalarvalues, plots, and other indicia or other viewable or user selectableelements. In one embodiment, they are displayed in a 3D mapping systemsuch as EnSite Velocity, which is commercially available from St. JudeMedical.

Generating a mapping with regard to color or other indicia such ashatching, shading, topographic representations, or symbols can beachieved by assigning a scalar value to a point in 3D space thatcorresponds to an electrode clique's centroid or the closest point onthe nearby cardiac surface. For example, a colored dot or triangle in 3Dspace or as a color mapped region on a cardiac surface can be displayedto an end user. These symbols correspond to the clique centroid's 3Dposition.

In addition, m-hat information such as m-hat directions can bevisualized or displayed to an end user to help interpret and improveuser perspective relative to a catheter coordinate frame. Similarly,display of indicia such as arrows, line segments, cylinders of otherinformation based on or correlated with m-hat can be used to improvecatheter navigation. These indicia can make it easier to interpretgeometry or maps in 3D NavX body coordinates. In one embodiment, theseindicia or user interface components are represented in a 2D or 3D spaceas arrows or simply line segments since, as mentioned above, the maximaldirections are ambiguous to ±180°. As shown in the user interfacefigures, the indicia or user interface components can be shown relativeto the catheter and/or relative to a generated GSM or other informationbeing displayed to an end user. All of these various embodiments can bedisplayed or used with a guide interface that is a representation ofelectrode grid and associated splines of a diagnostic catheter.

Various user interface components in the form of overlays, moveablescreen elements, panels, color maps, and plots alone or in combinationcan be presented to the end user. Typically, the user interfacecomponents can be selected or toggled using commands or by userselection with an interface device on the applicable user interface andsettings menu. In one embodiment, various user interface components canmoved around on the display screen, rotated, and docked at default oruser specified positions relative to other information displayed to theuser. These features can apply to the guide user interface and electricloop interface discussed below with regard to FIG. 15.

FIG. 11A is a user interface component that includes a guide userinterface having a grid array of thirty-six user selectable triangularcliques suitable for triggering a waveform signal display in response toeach clique selected. Any number of triangular cliques (1-36) can beselected with each triangular clique labeled T1 through T36. In someembodiments, signal values and scalar and m-hat values can be shownrelative to these selectable user interface elements such as by anoverlay on top of the triangular regions.

FIG. 11B is a user interface component that includes a guide userinterface having a grid array of nine user selectable square cliquessuitable for triggering waveform signal display in response to eachclique selected. Any number of square cliques can be selected (1-9) witheach square clique labeled SQ1 through SQ9. In some embodiments, signalvalues and scalar and m-hat values can be shown relative to theseselectable user interface elements such as by an overlay on top of thesquare regions. These overlays can include bipole values and other data.A select all (SA) interface is shown in the top left side of FIGS. 11and 11B. The SA interface allows for selection or un-selection of allcliques. The guide interfaces are typically color matched to anotherlegend or other displayed data such as color coded splines orcorresponding signals.

FIGS. 12A-12F are user interface components that includes a guide userinterface and waveforms displayed in response to the user selection ofvarious combinations of square and triangular cliques. With regard toFIGS. 12 A and 12B, user interface elements in the form of guide userinterfaces 400 and 405 are shown. Each user interface includesselectable graphical elements for triangular cliques (FIG. 12A) andsquare cliques (FIG. 12B). The selection of a single omnipolar cliquefor both triangular (FIG. 12A) and square (FIG. 12B) cliques is depictedhere. Triangular clique T21 and central square clique SQ5 have both beenselected by the user or in response to a programming command or script.A select all user interface toggle or button SA is shown, when selectedall cliques are selected and deselected respectively as shown, forexample, in FIGS. 12E and 12F.

A representation of a diagnostic catheter 407 in which the splines A, B,C, and D join in the catheter's shaft are seen oriented relative to theleft column having the same labeling. Thus, elements of the A row can becolored coded using the color yellow (Y), as shown by the one exemplarycell that is labeled. An exemplary element of the other rows is alsocolor coded using red (R), green (G), and blue (B). In some embodiments,all of the elements of a row are color coded or otherwise coded withsuitable indicia. Each interface provides a grid layout that is mappableto the grid of a given diagnostic catheter and its splines (rows). Foreach selected clique, such as for example triangular clique T21 orcentral square clique SQ5, the maximal bipolar electrogram signal isshown (called omni trace here). The reference signal generated using thesystem of FIG. 7 or otherwise is also shown as is the ECG trace. Whenall cliques are selected 36 and 9 traces are displayed as shown in FIGS.12E and 12F.

The triangle cliques are labeled T1-T36 as was shown in FIG. 11A. Thesquare cliques are labeled SQ1-SQ9 as was shown in FIG. 11B. Regions420, 425 on the left side of each figure and 422,427 on the right sideare bands or curtains that bound the central data region of interest forall of the signals shown.

In FIGS. 12C and 12D, two omnipolar cliques for both triangular andsquare cliques are depicted. Triangular clique T21 and central squareclique SQ5 have both been selected by the user or in response to aprogramming command or script. In addition, triangular clique T15 andsquare clique SQ2 also have both been selected. The solid triangularobject having a B on T15, T21, SQ5, and SQ2 indicates its constituentbipoles are to be shown (in addition to the omnipole trace) on the guideinterface. For each selected clique (solid triangular object) themaximal bipolar electrogram signal is shown (called omni trace here).Trace colors correspond to what is shown in the guide. In oneembodiment, the solid triangular object is color coded. In the exampleshown, the object is yellow. The traces in FIGS. 12A-12B are color codedusing P for purple, R for red, O for orange and G for green as shown onthe right side of the various traces. Other indicia can be used toidentify such objects in the interface.

T15 for example spans red and orange spline portions in interface 400.T21 for example spans green and orange spline portions in interface 400.Accordingly, in general, color maps of spline portions and omnipole,bipole, and unipole signals can be matched in various embodiments. Inaddition, whenever color or color maps are referenced, other mapping ortracking indicia can be used. Exemplary orange splines are shown with an“O” corresponding to the orange color. In some embodiments, all of thesplines are color coded or otherwise identified.

In FIGS. 12E and 12F, all cliques (36 triangles at left and 9 squaresright) result in display of all omnipolar waveforms in the mapacquisition window. The SA interface in the upper left corner of theguide is used to toggle between all and no selected cliques. In turn,trace colors (region below interfaces 400 and 405) correspond to theselected color for omnipole signals. In this interface layout, the colorselected is red and also identified by “R” as shown. Other colors andindicia can be used in lieu of the color red without limitation.

FIG. 13 is a user interface component that includes a color map basedguide to help locate ablation gaps using a V_(PP) map metric. Threecolor maps I, II and III are shown in the top figure. The interfaces aresimilar to those previously discussed herein in terms of there A-D rowlayout. Each color map or user interface element has three columns Left(L), Middle (M), and Right (R). Below each user interface I, II, and III(also labelled as 505, 515, and 525, respectively), a three-dimensionalview showing a GSM in 3D with a color coded voltage legend on the left.

The arrangement of user interfaces in FIG. 13 are suitable to help adiagnostic catheter user, such as an HD Grid user, locate ablation gapsusing V_(PP) map metric (3D GSM representations) shown on guide. Thecatheter can be maneuvered across and centered on the ablation line(ABL) (I and II) and then moved in the direction of the ablation line toidentify gaps (III) in the line. For clarity V_(PP) map colors are notalso shown on the model. Lesion markers 530 simply illustrate theintended continuous lesion ablation line that is being checked for gapsusing the V_(PP) color shown on the guide interface. In one embodiment,text or other indicia such can be used to alert a user to the possibleoccurrence of finding an ablation gap (ABG) or the ablation line (ABL).

FIG. 14 is a schematic diagram of a user interface that illustrates theeffect changes in catheter orientation angle have on voltagemeasurements. Two rows of omnipolar (omni) traces are shown as Omni 1and Omni 2. Each row of omni traces is derived from differentcharacteristic 2D loops as shown on the far right side in the column550. The upper loop corresponding to Omni trace 1 has less eccentricity,while the lower loop is tight and almost linear for Omni trace 2. Inaddition to the two rows of omnipolar traces and the set of loops 550,the changes to each signal for a given angular measure are shown incolumns 551, 553, and 555 with the associated angular measure beingdisplayed in the bottom third row.

Zero degree represents the major axis of the loop and is taken as them-hat maximal bipole direction. The zero degree orientation is shown incolumn 551. Moving from left to right, the figure shows omni tracesderived from each loop at a 0, 45 (column 553) and 90 degree orientation(column 555). Notice that the orientation change has a greater effect onthe Omni 2 signal amplitude compared to the Omni 1 signal amplitude.This results because the Omni 1 loop shape is not very eccentric. 2Dloops with high eccentricity are indicative of more homogenous wavefrontpropagation. In one embodiment, the guide user interface can displayeccentricity values for a given E-field loop as a diagnostic parameter.

FIG. 15 is a user interface display that includes a floating guideinterface and an electric field loop interface displayed as an overlayand a m-hat directional graphic element (green line segment 600). InFIG. 15, the line segment 600 is shown as a line dotted but this is anoptional representation. FIG. 15 includes several windows with guidediagram, loop and m-hat within loop display superimposed on thecatheter/surface/map display window (top left). The top left userinterface window shows a live surface and catheter map display. Thebottom left window shows scrolling waveforms of omnipole or bipolarsignals. In addition, the right most window shows user interfacesliders, toggles, and other controls. The middle column shows thetriggered map point acquisition window. Other windows and displays canbe zoomed, toggled, or otherwise saved to help with a diagnosticsession. The catheter 605 is also represented in the interface andincludes color coded splines. Periwinkle (P), green (G), red (R) andyellow (Y) are shown as the associated spline colors but other indiciacan be used in lieu of or in addition to color.

In addition with regard to the middle column or panel of the interfaceand the bottom left panel of the interface, various colors are used asindicium for the various traces shown. Other indicia and labels can beused in various embodiments. As shown in the foregoing middle and bottompanel B2-B3, B3-B4, B2-B3-C2-C3, +B2 and +B3 are identified by the colorred (R) or other suitable indicia. Similarly, B2-C2, B3-C3, and B4-C4are identified by the orange (O) or other suitable indicia. C1-C2,C2-C3, C3-C4, +C2 and +C3 are identified by the color green (G) or othersuitable indicia. B2-C1, C2-C3, B3-C2, B3-C4, B4-C3 and B2-C3 areidentified by the color periwinkle (P) or other suitable indicia.

In the top left window, a guide user interface (UI) is shown. The guideUI is generally free to be positioned over any part of the display. Inone embodiment, as part of the use interface element, catheter splinesin the guide interface/diagram are colored to match the same colors andsequence as the catheter in the display window (along splines A-D arecolors yellow (Y), red (R), green (G), and blue (B)). The across splinecolors are all orange (O) and the diagonal colors are periwinkle (P).Also, the dot 610 in the center clique indicates omnipoles are to becolored red. Other colors and indicia can be used without limitation.

Note the corresponding colors in the map acquisition window (the centerwindow) correspond to the color scheme of the guide interface. In thisexample, unipolar colors are also shown. Typically, unipole signalswould not be selected to appear in an OT voltage map. Although referenceto color maps and color is made throughout, in each instance otherindicia such as symbols or hatching or other differentiating userinterface features can be used. In one embodiment, the guide diagram orguide user interface can be toggled on/off, moved, overlaid and pinnedto persist anywhere on the display screen and respond to user actionsfrom one or more input devices.

FIG. 16 is a user interface display that shows activation directions andactivation regions using a color map and m-hat directional elements.M-hat values are shown as line segments 600 and are indicative of an OTvoltage mapping. These line segments may be green as shown or indicatedusing other indicia. The m-hat values generate information in the formof a maximal bipole axis at each OT clique. The line segments 600obtained provide a sense for activation directions and/or orientationsparticularly in healthy uniformly conducting tissue. In one embodiment,the m-hat values provide a constrained orientation relative to an axis.In one embodiment, the m-hat values can provide orientation informationand can also be combined with other information to provide directionalinformation with regard to activation.

As shown, pacing is from near the coronary sinus ostium. The activationof cardiac tissue tracks the timing legend on the left with green cloudshapes regions being activated first and purple regions being activatedlast. In this way, activation regions AR1-AR4 evolve in time as multipleregions undergo activation. A color coded legend ranging from −50 ms to100 ms is shown and can also be coded using hatching or other indicia.The legend starts in the white range, then pink, then red, then orange,then yellow, the green, then blue green, and finally purple. AR1 can beshown using a red color or other indicia. AR2 and AR3 are shown asdifferent colors in the green range of the vertical legend on the left.AR4 is shown as dark blue and transitioning to purple.

The line segments 600 are clustered in each activation region andcorrespond to maximal bipole axes which are ±180° ambiguous (so no arrowheads are shown). Arrow heads can be shown in various embodiments.Myocardial activation is similarly oriented to OT activation directionsin healthy tissue. Pink/Red color shows earliest and purple shows latestactivation across the RA, the progression of activation regions AR1 toAR4 tracks this color map. Green bipole axes shown as line segments 600are well aligned with the activation directions and show the benefit ofusing m-hat based metrics and the other related metrics describedherein.

Exemplary OT Applications, Methods and Further Exemplary Embodiments

Various UI features and display mapping can be used with the OT metricsto enhance diagrams of a catheter such as a high-density grid-basedcatheter in a static orientation that can be repositioned around thescreen. A guide diagram or interface can serve as a floating guide forthe purposes of assigning color to certain bipoles (e.g. across andomni) and their associated waveforms. Selecting one or more cliques(triangle or square) for display of their omnipole signals can beperformed using the guide interface. Further, the guide interfaceenables the display of a clique's constituent bipoles so the effect oforientation can be observed on omnipolar signals and peak-peak values.The guide interface also supports showing a color map version of voltageover the catheter. This allows one to readily identify high and lowvoltage areas and enables selection of the involved cliques foradditional scrutiny. It is desirable to investigate the origin ofunusual voltages independent of views that may be necessary to maintainor achieve a desired catheter location. A proximity indicator to allcatheter electrodes can be shown on the guide interface implemented inthe catheter-surface-map display window or in other windows and context.

In one embodiment, maximal bipole direction is ambiguous to ±1800. Inone embodiment, it is desirable to choose a direction and forcesubsequent arrows to be most compatible with that direction. This willaddress arrow flipping for voltage mapping in some instances.Alternatively consider a single large arrow for the whole of cathetercan be displayed should there be substantial agreement in alignment withm-hat (except for the ±180° issue).

Assigning color to certain bipoles (e.g. across and omni) and theirassociated waveforms can be implemented. This creates matching colors inthe guide diagram and the map acquisition window. By this, users canreadily distinguish among bipoles and omnipoles and readily understandwhich waveform type is being viewed.

Selecting one, multiple, or all cliques (triangle or square) for displayof their omnipole signals is a feature of the user interface design.Users may decide to focus on small or large numbers of cliques to lookinto atypical results and interpret them. For example, if the catheter'sproximal electrodes are or are not making contact with tissue a user canview the user interface and display features and view fractionatedsignals, to the extent they are present. This selection makes sense inthe geometric context of the guide diagram and other user interfacecomponents.

Enabling the display of a clique's constituent bipoles facilitatesobserving effect of orientation on bipolar signals and their peak-peakvalues. It also facilitates comparing them to the OT derived signal andits peak-peak value. Confidence in OT and an understanding ofdirectional effects may thus be obtained.

Showing a color map version of voltage over the catheter on the guideinterface allows one to readily identify high and low voltage areas andenable selection of the involved cliques is provided in one embodiment.In particular, it is useful to display a colored map of voltage on theguide diagram to provide users with a face-on view of the catheter suchthat every clique's voltage is clearly depicted. These are not oftenachieved in the catheter/surface/map display window as views necessaryfor catheter positioning may not be suited to a face-on view or becauseof the inclusion-exclusion criteria such as proximity to a cardiacsurface suppress visualization of voltage.

In one embodiment, to visualize the degree to which orientation affectsvoltage, a user control such as a rotatable knob with markings every 90degrees can be integrated with system 160 or as part of its UI. At 0degrees, the maximal bipoles are all shown as computed from theirindividual m-hat maximal bipole directions. As the knob is rotatedtoward 90 degrees, the bipole amplitudes will decrease (some more thanothers) and signal shapes change. At 90 degrees (m-hat_perp), thesignals will be near minimal and the degree to which their amplitudesare reduced is an index of loop eccentricity and how close propagationresembled a traveling wave. This is believed to help some usersunderstand directional effects as well and how OT employs projectionalong specific (maximal) directions.

Atrial Voltage Substrate in Atrial Flutter (or Macro Reentrant OrganizedAF)

The methods and systems can be used in the case of an AF ablation redowith the arrhythmia characterized by an atypical atrial flutter. Thismay be a macro reentrant arrhythmia in which case an ablation lineacross the reentrant circuit will terminate the arrhythmia. The catheterallows a user to become certain of the reentrant circuit using a singlemapping catheter, combining catheter orientation independent voltagewith maximal bipole direction assessments.

By sweeping catheter around in real-time, the clinician observes anarrow tract of conduction with high voltage, consistent directions,bordered by low voltage scar. In concert with the anatomy andconventions for such ablations, a line of block is planned. The narrowtract or isthmus is confirmed by checking that the low voltage bordersare not due to catheter orientation effects or lack of contact.Involvement of the isthmus is established by the relatively highvoltage, pattern of maximal bipole directions, and perhaps entrainmentpacing from a catheter bipole (with a post pacing interval essentiallyequal to the flutter cycle length). The clinical value is derived fromswift identification of the isthmus (which may itself be an ablationline gap) made sure by orientation independent assessments of voltagewith inspection of questionable areas.

Vector Field and Spatial Coherence Related Features

FIG. 17 is data representation diagram that includes two panels (A andB) of vector fields relative to a grid electrode representationgenerated using sinus rhythm (SR) and atrial fibrillation (AF)measurements, respectively. The third panel (C) of FIG. 17 includesentropy values determined with regard to vector groupings of therespective vector fields over ten heart cycles during SR and AF cycles.In general, the data represented in FIG. 17 can be generated using OTparameters such as m-hat and the other m-hat derived parametersdescribed herein. By comparing different cycles for both SR and AF,along with vector field, vector orientation and derived information, thedata representation of FIG. 17 illustrates various diagnostic featuressuch as assessing spatial coherence during AF and SR. Typically, thevector fields are generated using OT parameters described herein such asm-hat. As a result, they are referred to as OT vector fields. Othervector field representations not limited to m-hat or other relatedparameters can also be used in some embodiments.

As shown in FIG. 17, the representation of the vector fields and theirconstituent vectors effectively parameterize spatial and temporalorganization of vector fields during sinus rhythm and atrialfibrillation by determining their spatial entropies. As the vector fieldappears more chaotic and jumbled with varying vector orientations,entropy is increasing and spatial coherence is decreasing.

For each beat (in SR) or each cycle (in AF), an OT-vector field isgenerated within the mapping field being explored using a diagnosticcatheter. The spatial Entropy (E) of each OT-vector field is determinedusing the circular concentration parameter kappa or a scoring or rankingprocess such as the use of a histogram of the vector angles. During SR,in cycle 3, as shown by region 620, the vectors of the OT-vector fieldare trending in a shared direction and have similar angular deviations.This region 620 shows low entropy and high coherence. Conversely, duringAF, in cycle 2, for example, region 625 shows a cluster of vectorsexhibiting high entropy and low coherence.

For a given vector, its orientation relative to a reference line (forexample a 2D horizontal line) is recorded. For vectors collinear withthe reference line, the vector is assigned a 0° value. In areas wherethere is coherence or low entropy, clusters of vectors have the same orsimilar angular measures.

A uniform distribution of angles within the histogram indicates a highlydisorganized OT-vector field corresponding to high spatial entropyvalues. Conversely, if the histogram reflects a narrow range of angles,organization within the OT-vector field is indicated which correspondsto low spatial entropy. Spatial entropy may be determined by

$E = {- {\sum\limits_{i = 1}^{n}{{P( x_{i} )}\log_{b}{P( x_{i} )}}}}$

where P(x_(i)) is a probability density function obtained from thenumber of vectors in a specific angle bin i and n is the maximum numberof angle bins within the histogram. A log base 10 was used for thiscalculation. The average and standard deviation of entropy values aredetermined throughout 10 cycles or beats to obtain temporal entropy fromthe collection of spatial entropies. In panel C of FIG. 17, for thevarious canines used in the study (Dog 1-Dog 5), entropy values duringSR and AF over 10 cycles are depicted for SR and AF. The average entropyvalues are also shown.

In one embodiment, the organization of wave propagation can also beinferred from the vector fields shown. From FIG. 17, it is clear thatSR, with its characteristic spatial and temporal organization of wavepropagation, can be affirmed by the low vector field entropy values.During AF however, spatial and temporal disorganization of the vectorfields for these three consecutive cycles becomes evident.

FIG. 18 is a data representation diagram for three AF cycles that showsa vector field representation, a coherence grid derived from vectororientation, an indicia coded Vmax representation and an indicia codedrepresentation of populated Vmax values selected based on coherentvectors. The data representation of FIG. 18 illustrates an approach topopulate a mapping array using m-hat derived data during AF. In oneembodiment, this can be achieved by mapping a catheter electroderepresentation on an electro-anatomic map.

FIG. 18 illustrates the use of OT vector field coherence-based voltagemapping during SR or AF. For each beat (in SR) or each cycle (in AF), anOT-vector field is generated within the mapping field. A sub-field ofthe OT-vector field, a 2-by-2 grid that contains four OT unit vectors(e.g. speed is not taken into consideration; only direction is used) isselected for analysis. Within this sub-field, the average length of thefour OT unit vectors is determined and used as a spatial coherencescore.

If the score is close to 1, then that particular group of OT vectors isspatially coherent. However, if the score is close to 0 that group of OTvectors are spatially incoherent. The score of the four unit vectors isassigned to the spatial location of each of the original vectors withinthe 2-by-2 subfields. Spatial coherence evaluation is performedrepeatedly for all 2-by-2 subfields. In one embodiment, the evaluationis performed with subfields that overlap previously evaluated subfieldsbut include unevaluated vectors or different groupings of previouslyevaluated vectors.

For instances of vector overlap in subfields, the newly calculatedscores are added to the previously calculated scores. With all of thescores calculated and placed at their corresponding spatial location,they are scaled based on the number of overlaps occurring within anarea. Further, as part of this scaling, the central area with thegreatest number of overlaps has the highest scaling coefficients and thecorners with the least number of overlaps having the lowest scalingcoefficients. If the final coherence score is larger than 0.5, an areais marked with a green circle (see exemplary regions 630) or anotherindicia. Otherwise the area is marked with a red circle (or otherindicia) (see exemplary regions 635).

These markers (630, 635) assist in determining which parts of thepreviously created OT voltage maps are to be used to populate aresultant AF voltage map. Low coherence regions 635 are filtered out ornot selected. In contrast, coherent areas 630, are not filtered out orotherwise selected. The process is repeated for three or more cycles.Only those Vmax values that are consistently associated with spatiallycoherent vectors for all three cycles are used to populate a Vmaxvoltage map. This is but one selection criteria. Other selectioncriteria can be used. The adjusted Vmax row of FIG. 18 retains Vmax datafor the coherent vector regions 630 and removes the Vmax data for thenon-coherent vector regions 635. The populated Vmax values shown on theright of FIG. 18 includes the Vmax values that are filtered based onspatial coherence and by temporal consistency over the three cycles.These values range from about 0 to about 5, with the color coded legendprogressing from red, to yellow, to green, to light blue, and on to darkblue.

In light of the forgoing, the use of vector fields generated usingomnipoles and m-hat based approaches offers various diagnostic tools. Byusing the calculated vector field for each beat (or cycle), thecoherence of neighboring vector clusters can be quantified and evaluatedfor coherence. In turn, with the spatial coherence map it is possibleselectively filter voltage maps to only show electrically viableportions or Vmax areas of interest for further investigation. Further, acomparative evaluation or sum of the results of the coherence selectionover multiple cycles can be used to further refine the Vmax targetregions for consideration.

Scar Border Mapping and Ablation

Mapping scar borders in subjects with VT episodes is commonly done insinus rhythm because VT is often not well tolerated. It is also donebecause reentrant ischemic VT exit sites are commonly found along scarborders and are good ablation targets. Working with a catheter, a regionof low voltage may be encountered. The catheter is moved to straddle thehigh-low voltage transition as OT prevents confounding voltage withelectrode orientation. The pattern of voltage may be observed to be highalong splines A and B and low along splines C and D. This will often bebest seen in the guide diagram as not all cliques produce surface mappoints and the view angle in the catheter/surface/map display may bepoor.

Suspicious of poor contact along the C and D spline side, the clinicianrotates the distal catheter trying to bring C and D into better contact.If uniformly high voltage is then observed across catheter, this area isnot marked as scar border, reducing the likelihood of ablating healthymyocardium here. Conversely, if voltages remain low and smallfractionated potentials are seen supporting tissue contact, a scarborder has been defined. Confidence in voltage assessments depends on OTeliminating bipole orientation effects and by facilitating looking atthe constituent bipoles. Reliable assessments limiting ablation ofventricular pump muscle to locations where it may be involved in theclinical VT.

Ablation Gap Detection

Checking for gaps in ablation lines may not be as simple as putting acatheter in the pulmonary veins (PVs) and pacing from inside or outside.FIG. 13 shows one implementation of this use case. The catheter and OTvoltage mapping helps the clinician locate the ablation lines by notinga sharp transition of voltage and/or timing in their vicinity. With thelive voltage display, the clinician moves the catheter along the lineand quickly locates a potential low voltage gap.

Cliques at this gap are selected and reviewed to confirm that althoughsome orientation independent bipoles show low voltage, others just 2 mmaway show high voltage. This confirms identification of an ablation linegap and serves as a good ablation target. The location may be marked,the catheter withdrawn, and an ablation catheter positioned at the siteusing a 3D mapping system. By alternating ablation and diagnosticmapping catheters, the patient is subjected to a single cutaneousvascular access site. The diagnostic catheter locates this gap morequickly and with greater certainty than traditional methods.

The disclosure relates to various methods, systems, and apparatusrelating to electrical signal generation and detection in the form ofelectrograms, ECG signals, pacing signals, EP signals and other signalsand resultant detected signals and data that are collected or input withregard to a subject. In part, the disclosure includes embodiments andfeatures relating to orientation independent sensing such as describedin SYSTEMS AND METHODS FOR ORIENTATION INDEPENDENT SENSING filed on Nov.17, 2016 and having U.S. Patent Application Pub. No. 20160331471 theentire disclosure of which is incorporated herein by reference.

The use of arrow heads showing directionality in a given figure or thelack thereof are not intended to limit or require a direction in whichinformation can flow. For a given connector, such as the arrows andlines shown connecting the elements shown in FIG. 1A, for example,information can flow in one or more directions or in only one directionas suitable for a given embodiment, whether or not a connector includesan arrow head or is a bi-directional arrow. The connections can includevarious suitable data transmitting connections such as optical, wire,power, wireless, or electrical connections.

In general, although the use of color and various indicia are referencedand used throughout the application and figures, in each instance agiven color or indicia can be replaced with any suitable visualrepresentation or machine readable pattern. Accordingly, for example,colored lines, plots, user interface features, or other graphic elementsor indicia described herein or depicted in the figures can be replacedor with hatching, dotted lines, different colors or different indicia orgraphic elements without limitation.

Non-Limiting Software Features and Implementations for Disclosed OIS/OTEmbodiments

The following description is intended to provide an overview of devicehardware and other operating components suitable for performing themethods of the disclosure described herein. This description is notintended to limit the applicable environments or the scope of thedisclosure. Similarly, the hardware and other operating components maybe suitable as part of the apparatuses described above. The disclosurecan be practiced with other system configurations, computers,multiprocessor systems, microprocessor-based or programmable electronicdevices, network PCs, minicomputers, mainframe computers, and the like.

Some portions of the detailed description are presented in terms ofalgorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations can be used by those skilled in the computer andsoftware related fields. In one embodiment, an algorithm is here, andgenerally, conceived to be a self-consistent sequence of operationsleading to a desired result. The operations performed as methods stopsor otherwise described herein are those requiring physical manipulationsof physical quantities. Usually, though not necessarily, thesequantities take the form of electrical or magnetic signals capable ofbeing stored, transferred, combined, transformed, compared, andotherwise manipulated.

Unless specifically stated otherwise as apparent from the followingdiscussion, it is appreciated that throughout the description,discussions utilizing terms such as “processing” or “computing” or“calculating” or “comparing” or “pacing” or “detecting” or “tracing” or“sampling” “or “thresholding” or “operating” or “generating” or“determining” or “displaying” or “finding” or “extracting” or“filtering” or “excluding” or “interpolating” or “optimizing” or thelike, refer to the action and processes of a computer system, or similarelectronic data processing apparatus, that manipulates and transformsdata represented as physical (electronic) quantities within the computersystem's registers and memories into other data similarly represented asphysical quantities within the computer system memories or registers orother such information storage, transmission or display devices.

The present disclosure, in some embodiments, also relates to theapparatus for performing the operations herein. This apparatus may bespecially constructed for the required purposes, or it may comprise ageneral-purpose computer selectively activated or reconfigured by acomputer program stored in the computer.

The algorithms and displays presented herein are not inherently relatedto any particular computer or other apparatus. Various general purposesystems may be used with programs in accordance with the teachingsherein, or it may prove convenient to construct more specializedapparatus to perform the required method steps. The required structurefor a variety of these systems will appear from the description below.

Embodiments of the disclosure may be implemented in many differentforms, including, but in no way limited to, computer program logic foruse with a processor (e.g., a microprocessor, microcontroller, digitalsignal processor, or general purpose computer), programmable logic foruse with a programmable logic device, (e.g., a Field Programmable GateArray (FPGA) or other PLD), discrete components, integrated circuitry(e.g., an Application Specific Integrated Circuit (ASIC)), or any othermeans including any combination thereof.

Computer program logic implementing all or part of the functionalitypreviously described herein may be embodied in various forms, including,but in no way limited to, a source code form, a computer executableform, and various intermediate forms (e.g., forms generated by anassembler, compiler, linker, or locator). Source code may include aseries of computer program instructions implemented in any of variousprogramming languages (e.g., an object code, an assembly language, or ahigh-level language such as Fortran, C, C++, JAVA, or HTML) for use withvarious operating systems or operating environments. The source code maydefine and use various data structures and communication messages. Thesource code may be in a computer executable form (e.g., via aninterpreter), or the source code may be converted (e.g., via atranslator, assembler, or compiler) into a computer executable form.

The computer program may be fixed in any form (e.g., source code form,computer executable form, or an intermediate form) either permanently ortransitorily in a tangible storage medium, such as a semiconductormemory device (e.g., a RAM, ROM, PROM, EEPROM, or Flash-ProgrammableRAM), a magnetic memory device (e.g., a diskette or fixed disk), anoptical memory device (e.g., a CD-ROM), a PC card (e.g., PCMCIA card),or other memory device. The computer program may be fixed in any form ina signal that is transmittable to a computer using any of variouscommunication technologies, including, but in no way limited to, analogtechnologies, digital technologies, optical technologies, wirelesstechnologies (e.g., Bluetooth), networking technologies, andinternetworking technologies. The computer program may be distributed inany form as a removable storage medium with accompanying printed orelectronic documentation (e.g., shrink-wrapped software), preloaded witha computer system (e.g., on system ROM or fixed disk), or distributedfrom a server or electronic bulletin board over the communication system(e.g., the internet or World Wide Web).

Hardware logic (including programmable logic for use with a programmablelogic device) implementing all or part of the functionality previouslydescribed herein may be designed using traditional manual methods, ormay be designed, captured, simulated, or documented electronically usingvarious tools, such as Computer Aided Design (CAD), a hardwaredescription language (e.g., VHDL or AHDL), or a PLD programming language(e.g., PALASM, ABEL, or CUPL).

Programmable logic may be fixed either permanently or transitorily in atangible storage medium, such as a semiconductor memory device (e.g., aRAM, ROM, PROM, EEPROM, or Flash-Programmable RAM), a magnetic memorydevice (e.g., a diskette or fixed disk), an optical memory device (e.g.,a CD-ROM), or other memory device. The programmable logic may be fixedin a signal that is transmittable to a computer using any of variouscommunication technologies, including, but in no way limited to, analogtechnologies, digital technologies, optical technologies, wirelesstechnologies (e.g., Bluetooth), networking technologies, andinternetworking technologies.

The programmable logic may be distributed as a removable storage mediumwith accompanying printed or electronic documentation (e.g.,shrink-wrapped software), preloaded with a computer system (e.g., onsystem ROM or fixed disk), or distributed from a server or electronicbulletin board over the communication system (e.g., the internet orWorld Wide Web).

Various examples of suitable processing modules are discussed below inmore detail. As used herein a module refers to software, hardware, orfirmware suitable for performing a specific data processing or datatransmission task. In one embodiment, a module refers to a softwareroutine, program, or other memory resident application suitable forreceiving, transforming, routing performing feature extraction andprocessing instructions, or various types of data such as EP data,voltage differences, a relative extremum of differentialmagnitudes/values, reference triggers, visual and user interfaceoutputs, and other information of interest as described herein.Computers and computer systems described herein may include operativelyassociated computer-readable media such as memory for storing softwareapplications used in obtaining, processing, storing and/or communicatingdata. It can be appreciated that such memory can be internal, external,remote or local with respect to its operatively associated computer orcomputer system.

Memory may also include any means for storing software or otherinstructions including, for example and without limitation, a hard disk,an optical disk, floppy disk, DVD (digital versatile disc), CD (compactdisc), memory stick, flash memory, ROM (read only memory), RAM (randomaccess memory), DRAM (dynamic random access memory), PROM (programmableROM), EEPROM (extended erasable PROM), and/or other likecomputer-readable media.

In general, computer-readable memory media applied in association withembodiments of the disclosure described herein may include any memorymedium capable of storing instructions executed by a programmableapparatus. Where applicable, method steps described herein may beembodied or executed as instructions stored on a computer-readablememory medium or memory media. These instructions may be softwareembodied in various programming languages such as C++, C, Java, and/or avariety of other kinds of software programming languages that may beapplied to create instructions in accordance with embodiments of thedisclosure.

The aspects, embodiments, features, and examples of the disclosure areto be considered illustrative in all respects and are not intended tolimit the disclosure, the scope of which is defined only by the claims.Other embodiments, modifications, and usages will be apparent to thoseskilled in the art without departing from the spirit and scope of theclaimed disclosure.

The use of headings and sections in the application is not meant tolimit the disclosure; each section can apply to any aspect, embodiment,or feature of the disclosure.

Throughout the application, where compositions are described as having,including, or comprising specific components, or where processes aredescribed as having, including or comprising specific process steps, itis contemplated that compositions of the present teachings also consistessentially of, or consist of, the recited components, and that theprocesses of the present teachings also consist essentially of, orconsist of, the recited process steps.

In the application, where an element or component is said to be includedin and/or selected from a list of recited elements or components, itshould be understood that the element or component can be any one of therecited elements or components and can be selected from a groupconsisting of two or more of the recited elements or components.Further, it should be understood that elements and/or features of acomposition, an apparatus, or a method described herein can be combinedin a variety of ways without departing from the spirit and scope of thepresent teachings, whether explicit or implicit herein.

The use of the terms “include,” “includes,” “including,” “have,” “has,”or “having” should be generally understood as open-ended andnon-limiting unless specifically stated otherwise.

The use of the singular herein includes the plural (and vice versa)unless specifically stated otherwise. Moreover, the singular forms “a,”“an,” and “the” include plural forms unless the context clearly dictatesotherwise. In addition, where the use of the term “about” is before aquantitative value, the present teachings also include the specificquantitative value itself, unless specifically stated otherwise. As usedherein, the term “about” refers to a ±10% variation from the nominalvalue. As used herein, the term “substantially” refers to a ±10%variation from the nominal value.

It should be understood that the order of steps or order for performingcertain actions is immaterial so long as the present teachings remainoperable. Moreover, two or more steps or actions may be conductedsimultaneously.

Where a range or list of values is provided, each intervening valuebetween the upper and lower limits of that range or list of values isindividually contemplated and is encompassed within the disclosure as ifeach value were specifically enumerated herein. In addition, smallerranges between and including the upper and lower limits of a given rangeare contemplated and encompassed within the disclosure. The listing ofexemplary values or ranges is not a disclaimer of other values or rangesbetween and including the upper and lower limits of a given range.

Various embodiments are described herein to various apparatuses,systems, and/or methods. Numerous specific details are set forth toprovide a thorough understanding of the overall structure, function,manufacture, and use of the embodiments as described in thespecification and illustrated in the accompanying drawings. It will beunderstood by those skilled in the art, however, that the embodimentsmay be practiced without such specific details. In other instances,well-known operations, components, and elements have not been describedin detail so as not to obscure the embodiments described in thespecification. Those of ordinary skill in the art will understand thatthe embodiments described and illustrated herein are non-limitingexamples, and thus it can be appreciated that the specific structuraland functional details disclosed herein may be representative and do notnecessarily limit the scope of the embodiments, the scope of which isdefined solely by the appended claims.

Reference throughout the specification to “various embodiments,” “someembodiments,” “one embodiment,” or “an embodiment”, or the like, meansthat a particular feature, structure, or characteristic described inconnection with the embodiment is included in at least one embodiment.Thus, appearances of the phrases “in various embodiments,” “in someembodiments,” “in one embodiment,” or “in an embodiment”, or the like,in places throughout the specification are not necessarily all referringto the same embodiment. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments. Thus, the particular features, structures, orcharacteristics illustrated or described in connection with oneembodiment may be combined, in whole or in part, with the featuresstructures, or characteristics of one or more other embodiments withoutlimitation given that such combination is not illogical ornon-functional.

It will be appreciated that the terms “proximal” and “distal” may beused throughout the specification with reference to a clinicianmanipulating one end of an instrument used to treat a patient. The term“proximal” refers to the portion of the instrument closest to theclinician and the term “distal” refers to the portion located furthestfrom the clinician. It will be further appreciated that for concisenessand clarity, spatial terms such as “vertical,” “horizontal,” “up,” and“down” may be used herein with respect to the illustrated embodiments.However, surgical instruments may be used in many orientations andpositions, and these terms are not intended to be limiting and absolute.

It should be appreciated that various aspects of the claimed disclosureare directed to subsets and substeps of the techniques disclosed herein.Further, the terms and expressions employed herein are used as terms ofdescription and not of limitation, and there is no intention, in the useof such terms and expressions, of excluding any equivalents of thefeatures shown and described or portions thereof, but it is recognizedthat various modifications are possible within the scope of thedisclosure claimed. Accordingly, what is desired to be secured byLetters Patent is the disclosure as defined and differentiated in thefollowing claims, including all equivalents.

What is claimed is:
 1. A method of reducing one or more error types incardiac system data obtained from a subject using a plurality ofelectrodes, the method comprising: defining an error reducing vector{circumflex over (m)} by normalizing a differential electric fieldvector using a magnitude, wherein the differential electric field vectoris a difference of a first electric field vector E(t_(j)) and a secondelectric field vector E(t_(i)), wherein t_(i) and t_(j) are electricfield measurements in time, wherein t_(j)>t_(i) and wherein themagnitude is |E(t_(j))−E(t_(i))|; determining a cardiac system parameterby performing a vector operation comprising operating, using anoperator, upon (i) {circumflex over (m)} or a vector perpendicularthereto {circumflex over (m)}_(⊥) and (ii) a diagnostic vector, whereinthe diagnostic vector is generated using measured cardiac electrogramsignals to generate an output, wherein the output is a scalar output ora vector output; and displaying the output or information correlatedwith the output.
 2. The method of claim 1 further comprising maximizing|E(t_(j))−E(t_(i))|.
 3. The method of claim 1 wherein the operator is adot product operator, wherein the diagnostic vector is E(t), and whereinthe output of <{circumflex over (m)},E(t)> is a scalar electrical fieldsignal E_(m)(t).
 4. The method of claim 3 further comprising computing apeak to peak value of E_(m)(t).
 5. The method of claim 3 furthercomprising determining a scalar voltage signal V_(m)(t), whereinV_(m)(t) comprises a product of k and E_(m)(t), wherein k is anelectrode spacing between the plurality of electrodes.
 6. The method ofclaim 5 further comprising computing a peak to peak value of V_(m)(t).7. The method of claim 1 wherein the operator is a dot product operator,wherein the diagnostic vector is E(t), and wherein the output of({circumflex over (m)}_(⊥),E(t)) is a scalar electrical field signalE_(m⊥)(t).
 8. The method of claim 1 further comprising determining oneor more directional deviations between {circumflex over (m)} and â andgenerating an alert when the one or more directional deviations exceedsa threshold, wherein the direction of â is an activation direction. 9.The method of claim 8 wherein the threshold is an angular deviationbetween that ranges from about 15 degrees to about 20 degrees.
 10. Themethod of claim 1 wherein the one or more error types comprisesdirectionality-based errors and further comprising reducingdirectionality-based errors
 11. The method of claim 1 further comprisingdisplaying one or more graphic user interface elements aligned with{circumflex over (m)} relative to a 2D or 3D display of a cardiac tissuerepresentation.
 12. The method of claim 1 further comprising displayingthe one or more graphic user interface elements corresponding to oraligned with {circumflex over (m)} relative to one or more regions ofdetected cardiac tissue activation.
 13. The method of claim 1 furthercomprising displaying a graphic user interface element that comprises aplurality of user selectable elements, wherein the user selectableelements comprise a plurality of triangular electrode cliques and aplurality of square electrode cliques.
 14. The method of claim 13wherein, in response to user selection of one or more of the squareelectrode cliques or triangular electrode cliques, one or more waveformsassociated with each clique selected is displayed.
 15. The method ofclaim 13 wherein the graphic user interface element is a guide diagramcomprising a representation of an array of electrodes for a diagnosticcatheter and one or more indicia, wherein the indicia corresponds to aparameter selected from the group consisting of a bipole voltage, aunipole voltage, a unipole wave form, a bipole waveform, an ablationgap, and an activation direction.
 16. The method of claim 15 wherein theindicia is a color and further comprising displaying a color codedlegend comprising the color.
 17. A method of determining diagnosticinformation for a subject using a plurality of electrode-basedmeasurements, the method comprising: storing, in one or more electronicmemory storage devices, one or more sets of electrophysiological (EP)data received with regard to one or more tissues of the subject, whereinthe one or more sets comprise a first set of EP data; determining a setof electric field data from the first set of EP data, wherein the set ofelectric field data comprises a plurality of time varying electric fieldvectors; computing, for each pair of temporally adjacent electric fieldvectors of the plurality of time varying electric field vectors, adifference vector, wherein each difference vector has differentialmagnitude, identifying, from differential magnitudes of differencevectors, a relative extremum of the differential magnitudes, as a firstdifferential magnitude; defining a first diagnostic parameter,{circumflex over (m)}, wherein {circumflex over (m)} is proportional toor equal to the difference vector having the first differentialmagnitude; and displaying graphic user face element oriented along adirection of {circumflex over (m)}.
 18. The method of claim 17 furthercomprising determining a second diagnostic parameter is (i) using avector operator and {circumflex over (m)} or (ii) a vector correlatedwith {circumflex over (m)} or derived therefrom.
 19. A method ofgenerating a reference signal suitable for comparison to one or morecardiac tissue measured signals, the method comprising selecting aclique of connected unipoles in a non-linear arrangement; convertingcombination of selected unipoles and associated bipoles to electricfield components; and converting electric field components to electricalpotential signals V_(x) and V_(y), wherein x and y are axes of catheterreference frame.
 20. The method of claim 19 further comprising:normalizing V_(x) and V_(y) signals to generate a direction independentsignal.
 21. The method of claim 20 further comprising: filtering thedirection independent signal to generate a filtered directionindependent signal, wherein the filtered signal is directionallyindependent.
 22. The method of claim 21 wherein the step of filteringcomprises one or more steps selected from the group consisting ofreducing an error associated with detection of depolarizations, low passfiltering, differentiating, and signal thresholding.
 23. The method ofclaim 21 further comprising processing the filtered directionindependent signal using a refractory period of cardiac tissue, a noisefloor, and a zero-crossing detector to detect polarization events in thefiltered signal.
 24. The method of claim 20 wherein the normalizing stepcomprises determining a Euclidean magnitude.
 25. The method of claim 19wherein the step of converting the combination of selected unipoles andassociated bipoles is performed by performing a least squares fit. 26.The method of claim 1 further comprising measuring a plurality ofelectrical signals from cardiac tissue during atrial fibrillation andcharacterizing spatial coherence of a vector field derived using thecardiac system parameter.
 27. The method of claim 26 wherein the step ofcharacterizing is performed using a coherence or entropy measurement ofone or more vectors of the vector field.
 28. The method of claim 26wherein the step of characterizing is performed by coherence filteringVmax values on a per cycle basis and comparing filtered results for eachcycle to exclude inconsistent regions between different cycles.